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Ethanol-Injection Systems Explained
Thanks to the adoption of direct fuel injection, teaming gas and ethanol has the potential to beat diesel efficiency.
We can hear your groans already: Our federal government’s effort to curb oil imports by lacing gasoline with ethanol has been a boon to American farmers but a bust to the driving public. The problem is simple economics—pumping E85 (85-percent ethanol and 15-percent gasoline) into today’s flex-fuel cars costs more per mile than fueling the same car with regular gas. We’re suffering from ethanol’s detriments without exploiting its advantages.
Ethanol’s balance sheet has been well understood for decades. Because ethanol’s energy density is roughly 66 percent that of gasoline, mpg suffers when ethanol is used as a straight substitute. On the opposite side of the ledger, ethanol has an octane rating of 100, versus 85 to 100 for gasoline, enabling much higher compression ratios. (Unleaded, 100-octane racing gas is expensive and not widely distributed. Readily available premium gas tops out at 94 octane.) And when ethanol changes from liquid to gas on the way to combustion, it absorbs 2.6 times more heat than gasoline, a highly beneficial cooling effect. So how do we take advantage of those attributes to optimize ethanol’s role in modern transportation? The history books are a good place to start.
During World War II, BMW and Daimler-Benz sprayed methanol and water mixtures into their supercharged aircraft engines to forestall detonation (premature ignition of the fuel-air charge). In the U.S., a postwar GM applied similar research in its 1951 LeSabre dream car, which was powered by a supercharged V-8 capable of running on gas or methanol. That paved the way for the 1962 Oldsmobile F-85 Jetfire, the world’s first turbocharged production car, which used “Turbo-Rocket Fluid”—a mix of water, methanol, and rust inhibitor—to skirt detonation with a then-ambitious 10.25:1 compression ratio and 5.0 psi of boost.
Today’s racers use all manner of fluids—water, alcohol, nitromethane, lead substitutes, and nitrous oxide—in pursuit of power. There’s also a government-backed experiment at Chrysler aimed at running both gasoline and diesel fuels through the same engine. But the most sensible approach for the public at large is to use technology now in hand to achieve significant mpg gains. The tech? Gasoline, E85, and direct fuel injection.
British-based Ricardo and Ethanol Boosting Systems (EBS) of Cambridge, Massachusetts, both have E85-fueled engines under test that deliver diesel efficiency—at least 30-percent better than a typical gas engine—without the need for cumbersome, ultra-high-pressure fuel-injection and exhaust-treatment equipment.
Both firms propose aggressive turbocharging, a 12.0:1 or higher compression ratio, and about half the normal piston displacement. Ricardo uses an octane sensor, variable valve lift, and variations in valve and ignition timing to take maximum advantage of any ethanol pumped into the fuel tank. EBS adds a second complete fuel system that enables an engine to run on port-injected gas during cruising and direct-injected E85 only during full-load conditions to spare its consumption.
Heavy-duty pickups are the first candidates for this technology. Both EBS and Ricardo pitch their ethanol-based systems as diesel fighters capable of delivering 600 or more pound-feet of torque at low rpm from a 3.0-liter engine. Assuming that manufacturers agree with these ethanol boosters, the dual-fuel strategy could be handy for meeting the 35.5-mpg CAFE standard for 2020. By then, four-cylinder performance cars will be commonplace, and they’ll definitely be thirsty for all the Turbo-Rocket Fluid they can get.
Basics Of Options Trading Explained
Before we delve deep into the world of options trading, let’s take a moment to understand why do we need options at all. If you are thinking it is just another way to make money and was created by some fancy guys in suits working in Wall Street, well, you are wrong. The options world predates the modern stock exchanges by a large margin.
While some credit the Samurai for giving us the foundation on which options contracts were based, some actually acknowledge the Greeks for giving us an idea on how to speculate on a commodity, in this case, the harvest of olives. In both cases, humans were trying to guess the price of a food item and trade accordingly (rice in the case of samurais), long before the modern world put in various rules and set up exchanges.
With this in mind, let us try to answer the first question in your mind.
What is options trading?
Let’s take a very simple example to understand options trading. Consider that you are buying a stock for Rs. 3000. But the broker tells you about an exciting offer, that you can buy it now for Rs. 3000 or you can give a token amount of Rs. 30 and reserve the right to buy it at Rs. 3000 after a month, even if the stock increases in value at that time. But that token amount is non-refundable!
You realise that there is a high chance that the stock would cross Rs. 3030 and thus, you can breakeven at least. Since you have to pay only Rs. 30 now, the remaining amount can be used elsewhere for a month. You wait for a month and then look at the stock price.
Now, depending on the stock price, you have the option to buy the stock from the broker or not. Of course, this is an over-simplification but this is options trading in a gist.In the world of trading, options are instruments that belong to the derivatives family, which means its price is derived from something else, mostly stocks. The price of an option is intrinsically linked to the price of the underlying stock.
A formal definition is given below:
A stock option is a contract between two parties in which the stock option buyer (holder) purchases the right (but not the obligation) to buy/sell shares of an underlying stock at a predetermined price from/to the option seller (writer) within a fixed period of time.
We are going to make sure that by the end of this article you are well versed with the options trading world along with trying out a few options trading strategies as well. We will cover the following points in this article. If you feel that you want to skip the basics of options, then head straight to the options trading strategies.
Let’s start now, shall we!
Options trading vs. Stock trading
There must be a doubt in your mind that why do we even have options trading if it is just another way of trading. Well, here are a few points which make it different from trading stocks
- The Options contract has an expiration date, unlike stocks. The expiration can vary from weeks, months to years depending upon the regulations and the type of Options that you are practising. Stocks, on the other hand, do not have an expiration date.
- Unlike Stocks, Options derive their value from something else and that’s why they fall under the derivatives category
- Options are not definite by numbers like Stocks
- Options owners have no right (voting or dividend) in a company unlike Stock owners
It is quite often that some people find the Option’s concept difficult to understand though they have already followed it in their other transactions, for e.g. car insurance or mortgages. In this part of the article, we will take you through some of the most important aspects of Options trading before we get down to the world of options trading.
The Strike Price is the price at which the underlying stocks can be bought or sold as per the contract. In options trading, the Strike Price for a Call Option indicates the price at which the Stock can be bought (on or before its expiration) and for Put Options trading it refers to the price at which the seller can exercise its right to sell the underlying stocks (on or before its expiration)
Since the Options themselves don’t have an underlying value, the Options premium is the price that you have to pay in order to purchase an Option. The premium is determined by multiple factors including the underlying stock price, volatility in the market and the days until the Option’s expiration. In options trading, choosing the premium is one of the most important components.
In options trading, the underlying asset can be stocks, futures, index, commodity or currency. The price of Options is derived from its underlying asset. For the purpose of this article, we will be considering the underlying asset as the stock. The Option of stock gives the right to buy or sell the stock at a specific price and date to the holder. Hence its all about the underlying asset or stocks when it comes to Stock in Options Trading.
In options trading, all stock options have an expiration date. The expiration date is also the last date on which the Options holder can exercise the right to buy or sell the Options that are in holding. In Options Trading, the expiration of Options can vary from weeks to months to years depending upon the market and the regulations.
There are two major types of Options that are practised in most of the options trading markets.
- American Options which can be exercised anytime before its expiration date
- European Options which can only be exercised on the day of its expiration
Moneyness (ITM, OTM & ATM)
It is very important to understand the Options Moneyness before you start trading in Stock Options. A lot of options trading strategies are played around the Moneyness of an Option.
It basically defines the relationship between the strike price of an Option and the current price of the underlying Stocks. We will examine each term in detail below.
When is an Option in-the-money?
- Call Option – when the underlying stock price is higher than the strike price
- Put Option – when the underlying stock price is lower than the strike price
When is an Option out-of-the-money?
- Call Option – when the underlying stock price is lower than the strike price
- Put Option – when the underlying stock price is higher than the strike price
When is an Option at-the-money?
- When the underlying stock price is equal to the strike price.
Take a break here to ponder over the different terms as we will find it extremely useful later when we go through the types of options as well as a few options trading strategies.
Type of options
In the true sense, there are only two types of Options i.e Call & Put Options. We will understand them in more detail.
To Call or Put
A Call Option is an option to buy an underlying Stock on or before its expiration date. At the time of buying a Call Option, you pay a certain amount of premium to the seller which grants you the right (but not the obligation) to buy the underlying stock at a specified price (strike price).
Purchasing a call option means that you are bullish about the market and hoping that the price of the underlying stock may go up. In order for you to make a profit, the price of the stock should go higher than the strike price plus the premium of the call option that you have purchased before or at the time of its expiration.
In contrast, a Put Option is an option to sell an underlying Stock on or before its expiration date. Purchasing a Put Option means that you are bearish about the market and hoping that the price of the underlying stock may go down. In order for you to make a profit, the price of the stock should go down from the strike price plus the premium of the Put Option that you have purchased before or at the time of its expiration.
In this manner, both Put and Call option buyer’s loss is limited to the premium paid but profit is unlimited. The above explanations were from the buyer’s point of view. We will now understand the put-call options from the seller’s point of view, ie options writers. The Put option seller, in return for the premium charged, is obligated to buy the underlying asset at the strike price.
Similarly, the Call option seller, in return for the premium charged, is obligated to sell the underlying asset at the strike price. Is there a way to visualise the potential profit/loss of an option buyer or seller? Actually, there is. An option payoff diagram is a graphical representation of the net Profit/Loss made by the option buyers and sellers.
Before we go through the diagrams, let’s understand what the four terms mean. As we know that going short means selling and going long means buying the asset, the same principle applies to options. Keeping this in mind, we will go through the four terms.
- Short call – Here we are betting that the prices will fall and hence, a short call means you are selling calls.
- Short put – Here the short put means we are selling a put option
- Long call – it means that we are buying a call option since we are optimistic about the underlying asset’s share price
- Long put – Here we are buying a put option.
S = Underlying Price
X = Strike Price
Break-even point is that point at which you make no profit or no loss.
The long call holder makes a profit equal to the stock price at expiration minus strike price minus premium if the option is in the money. Call option holder makes a loss equal to the amount of premium if the option expires out of money and the writer of the option makes a flat profit equal to the option premium.
Similarly, for the put option buyer, profit is made when the option is in the money and is equal to the strike price minus the stock price at expiration minus premium. And, the put writer makes a profit equal to the premium for the option.
All right, until now we have been going through a lot of theory. Let’s switch gears for a minute and come to the real world. How do options look like? Well, let’s find out.
What does an options trading quote consist of?
If you were to look for an options quote on Apple stock, it would look something like this:
When this was recorded, the stock price of Apple Inc. was $196. Now let’s take one line from the list and break it down further.
In a typical options chain, you will have a list of call and put options with different strike prices and corresponding premiums. The call option details are on the left and the put option details are on the right with the strike price in the middle.
- The symbol and option number is the first column.
- The “last” column signifies the amount at which the last time the option was bought.
- “Change” indicates the variance between the last two trades of the said options
- “Bid” column indicates the bid submitted for the option.
- “Ask” indicates the asking price sought by the option seller.
- “Volume” indicates the number of options traded. Here the volume is 0.
- “Open Interest” indicates the number of options which can be bought for that strike price.
The columns are the same for the put options as well. In some cases, the data provider signifies whether the option is in the money, at the money or out of money as well. Of course, we need an example to really help our understanding of options trading. Thus, let’s go through one now.
Options Trading Example
We will go through two cases to better understand the call and put options.
For simplicity’s sake, let us assume the following:
- Price of Stock when the option is written: $100
- Premium: $5
- Expiration date: 1 month after the option is bought
The current price of stock: $110. Strike price: $120
The current price of stock: $120. Strike price: $110
Considering that we have gone through the detailed scenario of each option, how about we combine a few options together. Let’s understand an important concept which many professionals use in options trading.
What is Put-Call Parity In Python?
Put-call parity is a concept that anyone who is interested in options trading needs to understand. By gaining an understanding of put-call parity you can understand how the value of call option, put option and the stock are related to each other. This enables you to create other synthetic position using various option and stock combination.
The principle of put-call parity
Put-call parity principle defines the relationship between the price of a European Put option and European Call option, both having the same underlying asset, strike price and expiration date. If there is a deviation from put-call parity, then it would result in an arbitrage opportunity. Traders would take advantage of this opportunity to make riskless profits till the time the put-call parity is established again.
The put-call parity principle can be used to validate an option pricing model. If the option prices as computed by the model violate the put-call parity rule, such a model can be considered to be incorrect.
Understanding Put-Call Parity
To understand put-call parity, consider a portfolio “A” comprising of a call option and cash. The amount of cash held equals the call strike price. Consider another portfolio “B” comprising of a put option and the underlying asset.
S0 is the initial price of the underlying asset and ST is its price at expiration.
Let “r” be the risk-free rate and “T” be the time for expiration.
In time “T” the Zero-coupon bond will be worth K (strike price) given the risk-free rate of “r”.
Portfolio A = Call option + Zero-coupon bond
Portfolio B = Put option + Underlying Asset
If the share price is higher than X the call option will be exercised. Else, cash will be retained. Hence, at “T” portfolio A’s worth will be given by max(ST, X).
If the share price is lower than X, the put option will be exercised. Else, the underlying asset will be retained. Hence, at “T”, portfolio B’s worth will be given by max (ST, X).
If the two portfolios are equal at time, “T”, then they should be equal at any time. This gives us the put-call parity equation.
Equation for put-call parity:
C + Xe-rT = P + S0
In this equation,
- C is the premium on European Call Option
- P is the premium of European Put Option
- S0 is the spot price of the underlying stock
- And, Xe-rT is the current value (discounted value) of Zero-coupon bond (X)
We can summarize the payoffs of both the portfolios under different conditions as shown in the table below.
From the above table, we can see that under both scenarios, the payoffs from both the portfolios are equal.
Required Conditions For Put-call Parity
For put-call parity to hold, the following conditions should be met. However, in the real world, they hardly hold true and put-call parity equation may need some modifications accordingly. For the purpose of this blog, we have assumed that these conditions are met.
- The underlying stock doesn’t pay any dividend during the life of the European options
- There are no transaction costs
- There are no taxes
- Shorting is allowed and there are no borrow charges
Hence, put-call parity will hold in a frictionless market with the underlying stock paying no dividends.
In options trading, when the put-call parity principle gets violated, traders will try to take advantage of the arbitrage opportunity. An arbitrage trader will go long on the undervalued portfolio and short the overvalued portfolio to make a risk-free profit.
How to take advantage of arbitrage opportunity
Let us now consider an example with some numbers to see how trade can take advantage of arbitrage opportunities. Let’s assume that the spot price of a stock is $31, the risk-free interest rate is 10% per annum, the premium on three-month European call and put are $3 and $2.25 respectively and the exercise price is $30.
In this case, the value of portfolio A will be,
C+Xe-rT = 3+30e-0.1 * 3/12 = $32.26
The value of portfolio B will be,
P + S0 = 2.25 + 31 = $33.25
Portfolio B is overvalued and hence an arbitrageur can earn by going long on portfolio A and short on portfolio B. The following steps can be followed to earn arbitrage profits.
- Short the stock. This will generate a cash inflow of $31.
- Short the put option. This will generate a cash inflow of $2.25.
- Purchase the call option. This will generate cash outflow of $3.
- Total cash inflow is -3 + 2.25 + 31 = $30.25.
- Invest $30.25 in a zero-coupon bond with 3 months maturity with a yield of 10% per annum.
Return from the zero coupon bond after three months will be 30.25e 0.1 * 3/12 = $31.02.
If the stock price at maturity is above $30, the call option will be exercised and if the stock price is less than $30, the put option will be exercised. In both the scenarios, the arbitrageur will buy one stock at $30. This stock will be used to cover the short.
Total profit from the arbitrage = $31.02 – $30 = $1.02
Well, shouldn’t we look at some codes now?
Python Codes Used For Plotting The Charts
The below code can be used to plot the payoffs of the portfolios.
So far, we have gone through the basic concepts in options trading and looked at an options trading strategy as well. At this juncture, let’s look at the world of options trading and try to answer a simple question.
Why is Options Trading attractive?
Options are attractive instruments to trade in because of the higher returns. An option gives the right to the holder to do something, with the ‘option’ of not to exercise that right. This way, the holder can restrict his losses and multiply his returns.
While it is true that one options contract is for 100 shares, it is thus less risky to pay the premium and not risk the total amount which would have to be used if we had bought the shares instead. Thus your risk exposure is significantly reduced.However, in reality, options trading is very complex and that is because options pricing models are quite mathematical and complex.
So, how can you evaluate if the option is really worth buying? Let’s find out.
The key requirement in successful options trading strategies involves understanding and implementing options pricing models. In this section, we will get a brief understanding of Greeks in options which will help in creating and understanding the pricing models.
Options Pricing is based on two types of values
Intrinsic Value of an option
Recall the moneyness concept that we had gone through a few sections ago. When the call option stock price is above the strike price or when put option stock price is below the strike price, the option is said to be “In-The-Money (ITM)”, i.e. it has an intrinsic value. On the other hand, “Out of the money (OTM)” options have no intrinsic value. For OTM call options, the stock price is below the strike price and for OTM put options; stock price is above the strike price. The price of these options consists entirely of time value.
Time Value of an option
If you subtract the amount of intrinsic value from an options price, you’re left with the time value. It is based on the time to expiration. You can enroll for this free online options trading python course on Quantra and understand basic terminologies and concepts that will help you in options trading. We know what is intrinsic and the time value of an option. We even looked at the moneyness of an option. But how do we know that one option is better than the other, and how to measure the changes in option pricing. Well, let’s take the help of the greeks then.
Greeks are the risk measures associated with various positions in options trading. The common ones are delta, gamma, theta and vega. With the change in prices or volatility of the underlying stock, you need to know how your options pricing would be affected. Greeks in options help us understand how the various factors such as prices, time to expiry, volatility affect the options pricing.
Delta measures the sensitivity of an option’s price to a change in the price of the underlying stock. Simply put, delta is that options greek which tells you how much money a stock option will rise or drop in value with a $1 rise or drop in the underlying stock. Delta is dependent on underlying price, time to expiry and volatility. While the formula for calculating delta is on the basis of the Black-Scholes option pricing model, we can write it simply as,
Delta = [Expected change in Premium] / [Change in the price of the underlying stock]
Let’s understand this with an example for a call option:
We will create a table of historical prices to use as sample data. Let’s assume that the option will expire on 5th March and the strike price agreed upon is $140.
Thus, if we had to calculate the delta for the option on 2nd March, it would be $5/$10 = 0.5.
Here, we should add that since an option derives its value from the underlying stock, the delta option value will be between 0 and 1. Usually, the delta options creeps towards 1 as the option moves towards “in-the-money”.
While the delta for a call option increases as the price increases, it is the inverse for a put option. Think about it, as the stock price approaches the strike price, the value of the option would decrease. Thus, the delta put option is always ranging between -0 and 1.
Gamma measures the exposure of the options delta to the movement of the underlying stock price. Just like delta is the rate of change of options price with respect to underlying stock’s price; gamma is the rate of change of delta with respect to underlying stock’s price. Hence, gamma is called the second-order derivative.
Gamma = [Change in an options delta] / [Unit change in price of underlying asset]
Let’s see an example of how delta changes with respect to Gamma. Consider a call option of stock at a strike price of $300 for a premium of $15.
- Strike price: $300
- Initial Stock price: $150
- Delta: 0.2
- Gamma: 0.005
- Premium: $15
- New stock price: $180
- Change in stock price: $180 – $150 = $30
Thus, Change in Premium = Delta * Change in price of stock = 0.2 * 30 = 6.
Thus, new premium = $15 + $6 = $21
Change in delta = Gamma * Change in stock price = 0.005 * 30 = 0.15
Thus, new delta = 0.2 + 0.15 = 0.35.
Let us take things a step further and assume the stock price increases another 30 points, to $210.
New stock price: $210
Change in stock price: $210 – $180 = $30
Change in premium = Delta *Change in 0.35*30 = $10.5
Thus, new premium = $21 + $10.5 = $31.5
Change in delta = Gamma * Change in stock price = 0.005 * 30 = 0.15
Thus, new delta = 0.35 + 0.15 = 0.5.
In this way, delta and gamma of an option changes with the change in the stock price. We should note that Gamma is the highest for a stock call option when the delta of an option is at the money. Since a slight change in the underlying stock leads to a dramatic increase in the delta. Similarly, the gamma is low for options which are either out of the money or in the money as the delta of stock changes marginally with changes in the stock option.
Highest Gamma for At-the-money (ATM) option
Among the three instruments, at-the-money (ATM), out-of-the-money (OTM) and in-the-money (ITM); at the money (ATM) has the highest gamma. You can watch this video to understand it in more detail.
Theta measures the exposure of the options price to the passage of time. It measures the rate at which options price, especially in terms of the time value, changes or decreases as the time to expiry is approached.
Vega measures the exposure of the option price to changes in the volatility of the underlying. Generally, options are more expensive for higher volatility. So, if the volatility goes up, the price of the option might go up to and vice-versa.
Vega increases or decreases with respect to the time to expiry?
What do you think? You can confirm your answer by watching this video.
One of the popular options pricing model is Black Scholes, which helps us to understand the options greeks of an option.
Black-Scholes options pricing model
The formula for the Black-Scholes options pricing model is given as:
C is the price of the call option
P represents the price of a put option.
S0 is the underlying price,
X is the strike price,
σ represents volatility,
r is the continuously compounded risk-free interest rate,
t is the time to expiration, and
q is the continuously compounded dividend yield.
N(x) is the standard normal cumulative distribution function.
The formulas for d1 and d2 are given as:
To calculate the Greeks in options we use the Black-Scholes options pricing model.
Delta and Gamma are calculated as:
In the example below, we have used the determinants of the BS model to compute the Greeks in options.
At an underlying price of 1615.45, the price of a call option is 21.6332.
If we were to increase the price of the underlying by Rs. 1, the change in the price of the call, put and values of the Greeks in the option is as given below.
As can be observed, the Delta of the call option in the first table was 0.5579. Hence, given the definition of the delta, we can expect the price of the call option to increase approximately by this value when the price of the underlying increases by Rs.1. The new price of the call option is 22.1954 which is
Let’s move to Gamma, another Greek in option.
If you observe the value of Gamma in both the tables, it is the same for both call and put options contracts since it has the same formula for both options types. If you are going long on the options, then you would prefer having a higher gamma and if you are short, then you would be looking for a low gamma. Thus, if an options trader is having a net-long options position then he will aim to maximize the gamma, whereas in case of a net-short position he will try to minimize the gamma value.
The third Greek, Theta has different formulas for both call and put options. These are given below:
In the first table on the LHS, there are 30 days remaining for the options contract to expire. We have a negative theta value of -0.4975 for a long call option position which means that the options trader is running against time.
He has to be sure about his analysis in order to profit from trade as time decay will affect this position. This impact of time decay is evident in the table on the RHS where the time left to expiry is now 21 days with other factors remaining the same. As a result, the value of the call option has fallen from 21.6332 to 16.9 behaviour 319. If an options trader wants to profit from the time decay property, he can sell options instead of going long which will result in a positive theta.
We have just discussed how some of the individual Greeks in options impact option pricing. However, it is very essential to understand the combined behaviour of Greeks in an options position to truly profit from your options position. If you want to work on options greeks in Excel, you can refer to this blog.
Let us now look at a Python package which is used to implement the Black Scholes Model.
Python Library – Mibian
What is Mibian?
Mibian is an options pricing Python library implementing the Black-Scholes along with a couple other models for European options on currencies and stocks. In the context of this article, we are going to look at the Black-Scholes part of this library. Mibian is compatible with python 2.7 and 3.x. This library requires scipy to work properly.
How to use Mibian for BS Model?
The function which builds the Black-Scholes model in this library is the BS() function. The syntax for this function is as follows:
The first input is a list containing the underlying price, strike price, interest rate and days to expiration. This list has to be specified each time the function is being called. Next, we input the volatility, if we are interested in computing the price of options and the option greeks. The BS function will only contain two arguments.
If we are interested in computing the implied volatility, we will not input the volatility but instead will input either the call price or the put price. In case we are interested in computing the put-call parity, we will enter both the put price and call price after the list. The value returned would be:
(call price + price of the bond worth the strike price at maturity) – (put price + underlying asset price)
The syntax for returning the various desired outputs are mentioned below along with the usage of the BS function. The syntax for BS function with the input as volatility along with the list storing underlying price, strike price, interest rate and days to expiration:
Attributes of the returned value from the above-mentioned BS function:
The syntax for BS function with the input as callPrice along with the list storing underlying price, strike price, interest rate and days to expiration:
Attributes of the returned value from the above-mentioned BS function:
The syntax for BS function with the input as putPrice along with the list storing underlying price, strike price, interest rate and days to expiration:
Attributes of the returned value from the above-mentioned BS function:
The syntax for BS function with the inputs as callPrice and putPrice along with the list storing underlying price, strike price, interest rate and days to expiration:
Attributes of the returned value from the above-mentioned BS function:
While Black-Scholes is a relatively robust model, one of its shortcomings is its inability to predict the volatility smile. We will learn more about this as we move to the next pricing model.
Derman Kani Model
The Derman Kani model was developed to overcome the long-standing issue with the Black Scholes model, which is the volatility smile. One of the underlying assumptions of Black Scholes model is that the underlying follows a random walk with constant volatility. However, on calculating the implied volatility for different strikes, it is seen that the volatility curve is not a constant straight line as we would expect, but instead has the shape of a smile. This curve of implied volatility against the strike price is known as the volatility smile.
If the Black Scholes model is correct, it would mean that the underlying follows a lognormal distribution and the implied volatility curve would have been flat, but a volatility smile indicates that traders are implicitly attributing a unique non-lognormal distribution to the underlying. This non-lognormal distribution can be attributed to the underlying following a modified random walk, in the sense that the volatility is not constant and changes with both stock price and time. In order to correctly value the options, we would need to know the exact form of the modified random walk.
The Derman Kani model shows how to take the implied volatilities as inputs to deduce the form of the underlying’s random walk. More specifically a unique binomial tree is extracted from the smile corresponding to the random walk of the underlying, this tree is called the implied tree. This tree can be used to value other derivatives whose prices are not readily available from the market – for example, it can be used in standard but illiquid European options, American options, and exotic options.
What is the Heston Model?
Steven Heston provided a closed-form solution for the price of a European call option on an asset with stochastic volatility. This model was also developed to take into consideration the volatility smile, which could not be explained using the Black Scholes model.
The basic assumption of the Heston model is that volatility is a random variable. Therefore there are two random variables, one for the underlying and one for the volatility. Generally, when the variance of the underlying has been made stochastic, closed-form solutions will no longer exist.
But this is a major advantage of the Heston model, that closed-form solutions do exist for European plain vanilla options. This feature also makes calibration of the model feasible. If you are interested in learning about these models in more detail, you may go through the following research papers,
- Derman Kani Model – “The Volatility Smile and Its Implied Tree” by Emanuel Derman and Iraj Kani.
- Heston Model – “A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options”
So far, you have understood options trading and how to analyse an option as well as the pricing models used. Now, to apply this knowledge, you will need access to the markets, and this is where the role of a broker comes in.
Opening an options trading account
How to choose a broker for Options Trading?
Before we open an options trading account with a broker, let’s go over a few points to take into consideration when we choose a broker.
- Understand your aim when you tread the options trading waters, whether it is a way of hedging risk, as a speculative instrument, for income generation etc.
- Does the broker provide option evaluation tools of their own? It is always beneficial to have access to a plethora of tools when you are selecting the right option.
- Enquire the transaction costs or the commission charged by the broker as this will eat into your investment gains.
- Some brokers give access to research materials in various areas of the stock market. You can always check with the broker about access to research as well as subscriptions etc.
- Check the payment options provided by the broker to make sure it is compatible with your convenience.
Searching for the right broker
Once the required background research is done, you can choose the right broker as per your need and convenience. In the global market, a list of the top brokers is provided below:
List of Top International Brokers (Options Trading)
The list of top international options brokers is given below:
- E-trade ($0.65 per options contract)
- Ally Invest ($0.5 per contract traded)
- TD Ameritrade ($0.65 fee per contract)
- Interactive Brokers (starts at $0.25 per options contract)
- Schwab Brokerage ($0.65 per options contract)
List of Top Indian Brokers (Options Trading)
The list of top Indian options brokers is given below:
- ICICI Direct
- HDFC Securites
- Kotak Securities
- Angel Broking
- Axis Direct
Great! Now we look at some options trading strategies which can be used in the real world.
Options Trading Strategies
There are quite a few options trading strategies which can be used in today’s trading landscape. One of the most popular options trading strategies is based on Spreads and Butterflies. Let’s look at them in detail.
Spreads and Butterflies
Spreads or rather spread trading is simultaneously buying and selling the same option class but with different expiration date and strike price. Spread options trading is used to limit the risk but on the other hand, it also limits the reward for the person who indulges in spread trading.
Thus, if we are only interested in buying and selling call options of security, we will call it a call spread, and if it is only puts, then it will be called a put spread.
Depending on the changing factor, spreads can be categorised as:
- Horizontal Spread – Different expiration date, Same Strike price
- Vertical Spread – Same Expiration date, Different Strike price
- Diagonal Spread – Different expiration date, Different Strike price
Remember that an option’s value is based on the underlying security (in this case, stock price). Thus, we can also distinguish an option spread on whether we want the price to go up (Bull spread) or go down (Bear spread).
Bull call spread
In a bull call spread, we buy more than one option to offset the potential loss if the trade does not go our way.
Let’s try to understand this with the help of an example.
The following is a table of the available options for the same underlying stock and same expiry date:
Normally, if we have done the analysis and think that the stock can rise to $200, one way would be to buy a call stock option with a strike price of $180 for a premium of $15. Thus, if we are right and the stock reaches $200 on expiry, we buy it at the strike price of $180 and pocket a profit of ($20 -$15) = $5 since we paid the premium of $15.
But if we were not right and the stock price reaches $180 or less, we will not exercise the option resulting in a loss of the premium of $15. One workaround is to buy a call option at $180 and sell a call option for $200 at $10.
Thus, when the stock’s price reaches $200 on expiry, we exercise the call option for a profit of $5 (as seen above) and also pocket a profit of the premium of $10 since it will not be exercised by the owner. Thus, in this way, the total profit is ($5 + $10) = $15.
If the stock price goes above $200 and the put option is exercised by the owner, the increase in the profit from bought call option at $180 will be the same as the loss accumulated from the sold call option at $200 and thus, the profit would always be $15 no matter the increase in the stock price above $200 at expiry date.
Let’s construct a table to understand the various scenarios.
You can go through this informative blog to understand how to implement it in Python.
Bear put spread
The bull call spread was executed when we thought the stock would be increasing, but what if we analyse and find the stock price would decrease. In that case, we use the bear put spread.
Let’s assume that we are looking at the different strike prices of the same stock with the same expiry date.
One way to go about it is to buy the put option for the strike price of 160 at a premium of $15 while selling a put option for the strike price of $140 for the strike price of $10.
Thus, we create a scenario table as follows:
In this way, we can minimize our losses by simultaneously buying and selling options. You can go through this informative blog to understand how to implement it in Python.
A butterfly spread is actually a combination of bull and bear spreads. One example of the Butterfly Options Strategy consists of a Body (the middle double option position) and Wings (2 opposite end positions).
- Its properties are listed as follows:
- It is a three-leg strategy
- Involves buying or selling of Call/Put options (unlike Covered Call Strategy where a stock is bought and an OTM call option is sold)
- Can be constructed using Calls or Puts
- 4 options contracts at the same expiry date
- Have the same underlying asset
- 3 different Strike Prices are involved (2 have the same strike price)
- Create 2 Trades with these calls
Other Trading Strategies
We will list down a few more options trading strategies below:
We have covered all the basics of options trading which include the different Option terminologies as well as types. We also went through an options trading example and the option greeks. We understood various options trading strategies and things to consider before opening an options trading account.
If you have always been interested in automated trading and don’t know where to start, we have created a learning track for you at Quantra, which includes the. “Trading using Option Sentiment Indicators” course.
Disclaimer: All data and information provided in this article are for informational purposes only. QuantInsti ® makes no representations as to accuracy, completeness, currentness, suitability, or validity of any information in this article and will not be liable for any errors, omissions, or delays in this information or any losses, injuries, or damages arising from its display or use. All information is provided on an as-is basis.
How can I explain why phenol is acidic but ethanol is neutral in an aqueous solution?
a QN d zSkq FerRK b TM y FKG alG R AOVn a SSSZ g XXKkE i dKx n Fr g QH I B FrCq u phsg l KTBru l xej , QFqhn W L xm L yFTV C S
In phenols there is a benzene ring bonded to a hydroxyl group. The acidity of phenols is due to its ability to lose hydrogen ion to form phenoxide ions.
C6H5OH→ C6H5O¯ (phenoxide ion) + H +
In a phenol molecule, the sp2 hybridised carbon atom of benzene ring attached directly to the hydroxyl group acts as an electron withdrawing group and electron density decreases on oxygen atom. This results in the pulling of electron density towards the oxygen atom facilitating the removal of hydrogen as hydrogen ion. Resonance stabilized phenoxide ion is formed.
In the case of ethanol there is no such elec.
Comparison of Ethanol and Methanol Blending with Gasoline Using Engine Simulation
By Simeon Iliev
Submitted: January 29th 2020 Reviewed: October 1st 2020 Published: November 5th 2020
During the last years, concerns regarding climate change, decline of energy security, and hydrocarbon reserves have resulted in a wide interest in renewable alternative sources for transportation fuels. Methanol and ethanol have been possible candidates as alternative fuels for the internal combustion engines because they are liquid and have several physical and combustion properties which resemble those of gasoline. Therefore, the aim of this study is to develop the one-dimensional model of a gasoline engine for predicting the effect of various fuel types on engine performances, specific fuel consumption, and emissions. Commercial software AVL BOOST was used to examine the engine characteristics for different blends of methanol, ethanol, and gasoline (by volume). A comparison was made between the results gained from the engine simulation of different fuel blends and those of gasoline. They show that when blended fuel was used, the engine brake power decreased and the BSFC increased compared to those of gasoline fuel. When blended fuel increases, the CO and HC emissions decrease, and there is a major increase in NOx emissions when blended fuel increases up to 30% M30 (E30). Increase in the percentage of ethanol and methanol leads to a significant increase in NOx emissions.
- alternative fuels
- ethanol blends
- methanol blends
- engine simulation
- spark-ignition engine
chapter and author info
Simeon Iliev *
- Department of Engines and Vehicles, University of Ruse, Ruse, Bulgaria
*Address all correspondence to: [email protected]
From the Edited Volume
Edited by Mansour Al Qubeissi
In the last years, the problem with crude oil depletion has arisen. Intensive research has been carried out to find out alternative to fossil fuels. Alternative fuels are derived from resources different from petroleum. When used in internal combustion engines (ICE), these fuels generate lower air pollutants compared to petrol fuel, and a majority of them are more economically beneficial compared to fossils fuels. They are also renewable. The most common fuels that are used as alternative fuels are natural gas, propane, methanol, ethanol, and hydrogen. Regarding engine operating with blended fuels, a lot of papers have been written about these blended fuels; but a small number of works have compared some of these fuels together in the same engine [1, 2, 3, 4]. Low contents of ethanol or methanol have been added to gasoline since at least the 1970s, when there was a reduction in oil supplies and scientists began searching for alternative energy carriers in order to replace petrol fuels. In the beginning, ethanol and methanol were thought to be the most attractive alcohols to be added to gasoline. Ethanol and methanol can be manufactured from natural products or waste materials, whereas gasoline fuel which is a nonrenewable energy resource cannot be manufactured [5, 6]. An important feature is that methanol and ethanol can be used without requiring any significant changes in the structure of the engine. Being part of the various alcohols, ethanol and methanol are known as the most suitable fuels for spark-ignition (SI) engines.
The use of blended fuels is crucial since many of these blends can be used in engines with the aim to improve its performance, efficiency, and emissions. The oxygenates are one of the most important fuel additives to improve fuel efficiency (organic oxygen-containing compounds). A few oxygenates have been used as fuel additives, such as ethanol, methanol, methyl tertiary butyl alcohol, and tertiary butyl ether . The process of using oxygenates makes more oxygen available in the combustion process and has a great potential to reduce SI engine exhaust emissions.
Regarding the combustion process, the flash point and autoignition temperature of methanol and ethanol are higher than pure gasoline, which makes it safer for storage and transportation. The latent heat of ethanol of evaporation is three to five times higher than pure gasoline; this leads to increase the volumetric efficiency because temperature of the intake manifold is lower. The heating value of ethanol is lower than gasoline. Consequently, 1.6 times more alcohol fuel is needed to achieve the exact same energy output. The stoichiometric air-fuel ratio of ethanol is around two-third of the pure gasoline; therefore, for complete combustion, the needed amount of air is lesser for ethanol . Ethanol has several advantages compared to gasoline, e.g., lowering of unburned HC emissions, CO, and much better antiknock characteristics . Ethanol and methanol have a lot higher octane number compared to pure gasoline fuel . This enables higher compression ratios of engines and, as a result, increases its thermal efficiency . The production of methanol can be from natural gas at no great cost and is easy to blend with gasoline fuel. These properties of methanol make it as an attractive additive. Methanol is aggressive to some materials, like plastic components and some of the metals in the fuel system. When using methanol it is necessary that precautions had to be taken when handling it .
There are many publications with different blends of alcohols and gasoline fuel. For example, Palmer  examined the influence of blends of ethanol and gasoline in spark-ignition engine. The obtained results pointed out that ethanol addition (10%) leads to 5% increase in the engine power and 5% octane number increase for each 10% ethanol added. The result showed that 10% of ethanol addition to gasoline fuel lead to reduction the emissions of CO up to 30%. In another study, Bata et al.  examined different blends of ethanol and gasoline and discovered that ethanol reduced the UHC and CO emissions. The lowered CO emissions are caused by the oxygenated characteristic and wide flammability of ethanol. Other researchers  studied that the potentialities for ethanol production are equivalent to about 32% of the total gasoline consumption worldwide, when used in 85% ethanol in gasoline for a passenger vehicle. In another study, Shenghua et al.  examined a gasoline engine with various percentages of methanol blends (from 10 to 30%) in gasoline. The results showed that engine torque and power decreased, whereas the brake thermal efficiency improved with the increase of methanol percentage in the fuel blend. Other authors  have studied the influence of methanol-gasoline blends on the gasoline engine performance. The results showed that the highest brake mean effective pressure (BMEP) was obtained from 5% methanol-gasoline blend. In another study, Altun et al.  researched the influence of 5 and 10% methanol and ethanol blending in gasoline fuel on engine performance and emissions. The best result in emissions showed blended fuels. The HC emissions of E10 and M10 are reduced by 13 and 15% and the CO emissions by 10.6 and 9.8%, respectively. An increased CO2 emission for E10 and M10 was observed. The methanol and ethanol addition to gasoline showed an increase in the brake-specific fuel consumption (BSFC) and a decrease in break thermal efficiency compared to gasoline.
It can be seen in the literature survey that the exhaust emissions for ethanol-gasoline and methanol-gasoline blends are lower than that of pure gasoline fuel [9, 13, 14, 17]. The engine performance and exhaust emissions with ethanol-gasoline blends resemble those with methanol-gasoline blends.
From the reviewed literature, a conclusion was made that the exhaust emission and engine performance of various blends of methanol and ethanol in gasoline engines have not been investigated sufficiently. Therefore, the objective of this work is to investigate the effects of methanol-gasoline and ethanol-gasoline fuel blends on the performance and exhaust emissions of a gasoline engine under various engine speeds, comparing them with those of pure gasoline.
The simulation tools are the most used in recent years owing to the continuous increase in computational power. The use of engine simulations enables optimization of engine combustion, geometry, and operating characteristics toward improving specific fuel consumption and exhaust emissions and reducing engine development time and costs. Consequently, it can be expected that the use of engine simulations during engine construction will continue to increase. Engine modeling is a fruitful research area, and therefore many laboratories have their own engine thermodynamic models with varying degrees of complexity, scope, and ease to use .
Computer simulation is becoming an important tool for time and cost efficiency in engine’s development. The simulation results are challenging to be obtained experimentally. Using computational fluid dynamics (CFD) has allowed researchers to understand the flow behavior and quantify important flow parameters such as mass flow rates or pressure drops, under the condition that the CFD tools have been properly validated against experimental results. Many processes in the engine are three-dimensional; however, it requires greater knowledge and large computational time. Thus, simplified one-dimensional simulation is occasionally used. Hence, simulating the complex components by means of a three-dimensional code and modeling the rest of the system with a one-dimensional code are the right choice to save computational time, i.e., the ducts. This way, a coupling methodology between the one-dimensional and the three-dimensional codes in the respective interfaces is necessary and has become the aim of numerous authors [19, 20, 21].
2. Research methodology
The aim of the present chapter is to develop the one-dimensional model of four-stroke port fuel injection (PFI) gasoline engine for predicting the effect of methanol-gasoline (M0–M50) and ethanol-gasoline (E0–E50) addition to gasoline on the exhaust emissions and performance of gasoline engine. For this, simulation of gasoline SI engine (calibrated) as the basic operating condition and the laminar burning velocity cor relations of methanol-gasoline and ethanol-gasoline blends for calculating the changed combustion duration was used. The engine power, specific fuel consumption, and exhaust emissions were compared and discussed [22, 23].
2.1. Simulation setup
The one-dimensional SI engine model is created by using the AVL BOOST software and has been employed to examine the performance and emissions working on gasoline, ethanol-gasoline, and methanol-gasoline blends.
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In Figure 1, PFIE symbolizes the engine, while C1–C4 is the number of cylinders of the SI engine. The cylinders are the main element in this model, because they have many very important parameters to settle: the internal geometry, bore, stroke, connecting rod, length and compression ratio, as well as the piston pin offset and the mean crankcase pressure. The measuring points are marked with MP1–MP18. PL1–PL4 symbolizes the plenum. System boundary stands for SB1 and SB2. CL1 represents the cleaner. R1–R10 stands for flow restrictions. CAT1 symbolizes catalyst and fuel injectors—I1–I4. The flow pipes are numbered 1–34.
Schematic of the gasoline PFI engine model.
The calibrated gasoline engine model was described by Iliev , and its layout is shown in Figure 1 with engine specification shown in Table 1.
|Connection rod length||143.5 (mm)|
|Number of cylinder||4|
|Piston pin offset||0 (mm)|
|Intake valve open||20 BTDC (deg)|
|Intake valve close||70 ABDC (deg)|
|Exhaust valve open||50 BBDC (deg)|
|Exhaust valve close||30 ATDC (deg)|
|Piston surface area||5809 (mm 2 )|
|Cylinder surface area||7550 (mm 2 )|
|Number of stroke||4|
Table 2 presents a comparison between the properties of gasoline, ethanol, and methanol. As shown in Table 2, compared with gasoline and ethanol, methanol has a higher elemental oxygen content and a lower heating value, molecular weight, elemental carbon, hydrogen content, and stoichiometric air/fuel ratio (AFR).
|Oxygen content (wt%)||—||49.93||34.73|
|Carbon content (wt%)||86.3||37.5||52.2|
|Hydrogen content (wt%)||24.8||12.5||13.1|
|Lower heating value (MJ/kg)||44.3||20||27|
|Heat of evaporation (kJ/kg)||305||1.178||840|
|Research octane number||96.5||112||111|
|Motor octane number||87.2||91||92|
|Vapor pressure (psi at 37.7 OC)||4.5||4.6||2|
|Destiny (g/cm 3 )||0.737||0.792||0.785|
|Normal boiling point (OC)||38–204||64||78|
|Autoignition temperature (OC)||246–280||470||365|
Comparison of fuel properties.
2.2. Combustion model description
In this research, two-zone model of Vibe was chosen for the combustion simulation and analysis. The combustion chamber was divided into two regions: unburned gas region and burned gas regions . For the burned charge and unburned charge, the first law of thermodynamics is applied:
where dm u represents the change of the internal energy in the cylinder, p c dV da is the piston work, dQ F da stands for the fuel heat input, dQ W da is the wall heat loses, h u dm b da represents the enthalpy flow from the unburned to the burned zone due to the conversion of a fresh charge to combustion products. The heat flux between the two zones is neglected. h BB dm BB da is the enthalpy flow due to blow-by, u and b in the subscript are unburned and burned gas.
Moreover, the sum of the zone volumes must be equal to the cylinder volume, and the sum of the volume changes must be equal to the cylinder volume change:
The amount of burned mixture at each time setup is obtained from the Vibe function. For all other terms, for instance, wall heat losses, etc., models similar to the single-zone models with an appropriate distribution on the two zones are used .
2.3. A description of exhaust emission model
In AVL BOOST, the model of formation on NOx is based on AVL List Gmbh , which incorporates the Zeldovich mechanism . The rate of NOx production was obtained using Eq. (5):
where α = C NO . act C NO . equ . 1 C KM , AK 2 = r 1 r 2 + r 3 , AK 4 = r 4 r 5 + r 6 .
In the above equation, C PPM represents post-processing multiplier, C KM denotes kinetic multiplier, C stands for molar concentration in equilibrium, and r i represents reaction rates of Zeldovich mechanism.
The NOx formation model in AVL Boost is based on Onorati et al. :
In Eq. (6), C represents molar concentration in equilibrium and r i represents reaction rates based on the model.
The unburned HC has different sources. A complete description of HC formation still cannot be given, and the achievement of a reliable model within a thermodynamic approach is definitely prevented by the fundamental assumptions and the requirement of reduced computational times. Still, a phenomenological model which accounts for the main formation mechanisms and is able to capture the HC trends as function of the engine operating parameter may be proposed. The following important sources of unburned HC can be identified in SI engines :
During the intake and compression stroke, fuel vapor is absorbed into the oil layer and deposits on the cylinder walls. The following desorption occurs when the cylinder pressure decreases during the expansion stroke and complete combustion cannot take place anymore.
A fraction of the charge enters the crevice volumes and is not burned since the flame quenches at the entrance.
Occasional complete misfire or partial burning takes place when combustion quality is poor.
Quench layers on the combustion chamber wall which are left as the flame extinguishes prior to reaching the walls.
The flow of fuel vapor into the exhaust system during valve overlap in gasoline engines.
The first two mechanisms and in particular the crevice formation are considered to be the most important and need to be accounted for in a thermodynamic model. Partial burn and quench layer effect cannot be physically described in a quasi-dimensional approach, but may be included by adopting tunable semiempirical correlations.
The formation of unburned HC in the crevices is described by assuming that the pressure in the cylinder and in the crevices is the same and that the temperature of the mass in the crevice volumes is equal to the piston temperature.
The mass in the crevices at any time is described by Eq. (7):
In Eq. (7), m crevice represents the mass of unburned charge in the crevice, p denotes cylinder pressure, V crevice stands for total crevice volume, M represents unburned molecular weight, T piston is the temperature of the piston, and R denotes gas constant.
The second important source of HC is the presence of lubricating oil in the fuel or on the walls of the combustion chamber. During the compression stroke, the fuel vapor pressure increases so, by Henry’s law, absorption occurs even if the oil was saturated during the intake. During combustion the concentration of fuel vapor in the burned gases goes to zero so the absorbed fuel vapor will desorb from the liquid oil into the burned gases. Fuel solubility is a positive function of the molecular weight, so the oil layer contributed to HC emissions depending on the different solubility of individual hydrocarbons in the lubricating oil.
The assumptions made in the development of the HC absorption/desorption are the following:
Fuel is constituted by a single hydrocarbon species, completely vaporized in the fresh mixture.
The oil film temperature is at the same as the cylinder wall.
Traverse flow across the oil film is negligible.
Oil is represented by squalane (C30H62), whose characteristics resemble those of the SAE5W20 lubricant.
Diffusion of the fuel in the oil film is the limiting factor, for the diffusion constant in the liquid phase which is 104 times smaller than the corresponding value in the gas phase.
The radial distribution of the fuel mass fraction in the oil film can be determined by solving the diffusion Eq. (8):
In Eq. (8), w F represents fuel’s mass fraction in the oil film, t is the time, r stands for radial position in the oil film (distance from the wall), and D is relative (fuel-oil) diffusion coefficient.
3. Result and discussion
The present research focused on the performance and emission characteristics of the methanol and ethanol-gasoline blends. Various concentrations of the blends 0% methanol (ethanol) M0 (E0), 5% methanol (ethanol) M5 (E5), 10% methanol (ethanol) M10 (E10), 20% methanol (ethanol) M20 (E20), 30% methanol (ethanol) M30 (E30), 50% methanol (ethanol) M50 (E50), and 85% methanol (ethanol) M85 (E85) by volume were analyzed.
3.1. Engine performance characteristics
The results of the brake power and specific fuel consumption for ethanol-gasoline blended fuels at different engine speeds are shown on Figures 2 and 3.
Influence of ethanol-gasoline blended fuels on brake power.
Influence of ethanol-gasoline blended fuels on brake-specific fuel consumption.
The brake power is one of the important factors that determine the performance of an engine. The variation of brake power with speed was obtained at full load conditions for E5, E10, E20, E30, E50, and pure gasoline E0. The ethanol content in the blended fuel increased, and the brake power decreased for all engine speeds. The gasoline brake power was higher than E5–E50 for all engine speeds. The ethanol’s heat of evaporation is higher in comparison to gasoline fuel, providing air-fuel charge cooling and increasing the density of the charge. The blended fuel causes the equivalence ratio of blend approaches to stoichiometric condition which can lead to a better combustion. However, the ethanol heating value is lower compared to gasoline, and it can neutralize the previous positive effects. Consequently, a lower power output is obtained.
Figure 3 shows the changes of the BSFC for ethanol-gasoline blends under various engine speeds. The figure shows that the BSFC increased as the ethanol percentage increased. Heating value and stoichiometric air-fuel ratio are the smallest for these two fuels, which means that for specific air-fuel equivalence ratio, more fuel is needed. The highest specific fuel consumption is obtained at E50 ethanol-gasoline blend.
Moreover, there is a slight difference between the BSFC when using pure gasoline and when using blends (E5, E10, and E20). The lower energy content of blended fuels causes some increment in BSFC of the engine.
Figure 4 shows the influence of methanol-gasoline blended fuels on engine brake power. The variation of brake power with speed was obtained at full load conditions for M5, M10, M20, M30, M50, and pure gasoline M0. When the methanol content in the blended fuel was increased (M10, M20, and M30), there was not a significant increase in engine brake power.
Influence of methanol-gasoline blended fuels on brake power.
The engine brake power may be due to the increase of the indicated mean effective pressure for higher methanol content blends. The methanol’s heat of evaporation is higher compared to that of gasoline, thus providing air-fuel charge cooling and increasing the density of the charge. Therefore, a higher power output is obtained. The engine brake power was higher in operation with gasoline in comparison to M50 for all engine speeds.
Figure 5 shows the variations of the BSFC for methanol-gasoline blended fuels under various engine speeds. As shown in this figure, the BSFC increased as the methanol percentage increased. This can be described with heating value, and stoichiometric air-fuel ratio is the smallest for these two fuels, which means that for specific air-fuel equivalence ratio, more fuel is needed. The specific fuel consumption of M50 methanol-gasoline blend was highest compared to those of gasoline for all engine speeds.
Influence of methanol-gasoline blended fuels on engine brake power.
Furthermore, there is a small difference between the BSFC when using gasoline and when using methanol-gasoline blended fuels (M5–M30). As engine speed increased reaching 2000 rpm, the BSFC decreased reaching its minimum value.
The results of the brake power and specific fuel consumption for ethanol- and methanol-gasoline blended fuels at different engine speeds are presented in Figures 6 and 7.
Effect of blended fuels on engine brake power.
Influence of blended fuels on engine fuel consumption.
When there was an increase in the ethanol content in the blended fuel, the brake power decreased for all engine speeds. The brake power of gasoline fuel was higher than those of E5–E50. The heating value of ethanol is lower than pure gasoline fuel, and the heating value of the blends decreases with the increase of the ethanol percentage. Consequently, a lower power output is obtained [22, 23].
By increasing the percentage of methanol in the blends (M5 and M10), the brake power slightly increased, which can be explained by better combustion efficiency of oxygenated fuels. By increasing the methanol content in the blends (M30 and M50), the engine brake power decreased for all engine speeds. The blended fuel heating value decreases with the increase of the percentage of methanol. This results in a lower power output. The gasoline brake power was higher compared to blend M50.
Figure 7 shows the changes of the BSFC for blended fuels under different engine speeds. The BSFC increased as the ethanol and methanol percentage increased. The reason has been known—the heating value and stoichiometric air-fuel ratio are the smallest for this fuel, which means that more fuel is needed for specific air-fuel equivalence ratio. The highest specific fuel consumption is obtained at E50 (M50) blended fuel.
What is more, there is small difference between the BSFC when using pure gasoline and blended fuels (E5 (M5), E10 (M10), and E20 (M20)). The lower energy content of ethanol blended fuels makes some increment in BSFC.
3.2. Emission characteristics
The result of the ethanol-blended fuels on CO emissions is shown in Figure 8.
Influence of ethanol-gasoline blended fuels on CO emissions.
A conclusion, which can be made by Figure 8, is that when ethanol content increases, the CO emission decreases. The reason for this could be explained with the enrichment of oxygen owing to the ethanol, in which an increase in the proportion of oxygen will promote the further oxidation of CO during the engine exhaust process. One of the other significant reasons for this reduction is that ethanol (C2H5OH) has less carbon than gasoline (C8H18).
The result of the ethanol gasoline blends on HC emissions is shown in Figure 9. The figure shows that when ethanol percentage increases, the HC concentration decreases. The HC emission decreases with the increase of the relative air-fuel ratio. The decrease of HC can be explained similarly to that of CO concentration described above.
Influence of ethanol-gasoline blended fuels on HC emissions.
The effect of the ethanol gasoline blends on NOx emissions for various engine speeds is shown in Figure 10. When the combustion process is closer to stoichiometric, flame temperature increases. As a result, the NOx emissions are increased.
Influence of ethanol-gasoline blended fuels on NOx emissions.
The effect of the methanol-gasoline blends on CO emissions for various engine speeds can be seen in Figure 11. When methanol percentage increases, the CO concentration decreases. This can be explained with the enrichment of oxygen because of the methanol and less carbon of methanol than gasoline.
Influence of methanol-gasoline blended fuels on CO emissions.
The effect of the methanol-gasoline blends on HC emissions is visible in Figure 12. When methanol percentage increases, the HC concentration decreases. The concentration of HC emissions decreases with the increase of the relative air-fuel ratio. The reason for the decrease of HC concentration resembles that of ethanol.
Influence of methanol-gasoline blended fuels on HC emissions.
The effect of the methanol-gasoline blends on NOx emissions can be seen in Figure 13. When methanol percentage increases, the NOx concentration increases. When combustion process is closer to stoichiometric, flame temperature increases and the NOx emissions increase as well.
Influence of methanol-gasoline blended fuels on NOx emissions.
The effect of the ethanol- and methanol-gasoline blends on CO emissions can be viewed in Figure 14. By increasing the methanol and ethanol content in the blended fuel, the CO emission decreases. The reason can be the enrichment of oxygen because of the ethanol and methanol, in which an increase in the proportion of oxygen will promote the further oxidation of CO during the engine exhaust process. Another major reason for this reduction is that ethanol (C2H5OH) and methanol (CH3OH) have less carbon than gasoline (C8H18). The lowest CO emissions are obtained with blended fuel containing methanol (M50).
Influence of ethanol- and methanol–gasoline blended fuels on CO emissions.
The effect of the ethanol- and methanol-gasoline blends on HC emissions is visible in Figure 15. When there is an increase in the ethanol and methanol percentage, the HC concentration decreases.
Influence of blended fuels on HC and NOx emissions.
When the relative air-fuel ratio increases, the concentration of HC emissions decreases. The reason for the decrease in HC emissions is similar to that of CO described above. The comparison between the decrease in HC emissions and the blended fuels indicates that methanol is more effective than ethanol. The lowest HC emissions are obtained with methanol-blended fuel (M50). When more combustion is complete, it will result in lower HC emissions.
Figure 15 shows the influence of the blended fuels on NOx emissions. It is noticeable that when methanol and ethanol percentage increases up to 30% E30 (M30), the NOx emission increases, after which it decreases with increasing the percentage of the methanol (ethanol).
The reason is that the improved combustion results in increased temperature in combustion chamber. The higher methanol (ethanol) content in the blends lowers the temperature in combustion chamber. The lower temperature is due to:
Latent heat of evaporation of alcohols, which decreases the temperature in combustion chamber during the vaporization.
The more triatomic molecules are produced: the higher the gas heat capacity and the lower the combustion gas temperature will be. However, the low temperature in combustion chamber can also lead to an increment in the unburned combustion product.
The purpose of the present chapter is to demonstrate the influence of ethanol and methanol addition to gasoline on spark-ignition engine performance and emission characteristics. The summarized results from this study are the following:
With the increase of the percentage of ethanol in the blended fuel, the engine brake power decreased for various engine speeds.
With the increase of the percentage of methanol in the blends M5 and M10, the brake power slightly increased, and with the increase of the percentage of methanol in the blends M30 and M50, the brake power decreased.
As the ethanol (methanol) percentage increased, the BSFC increased. The blended fuels show higher BSFC and lower engine brake power than pure gasoline. Furthermore, there is a slight difference between the BSFC in comparison of gasoline and gasoline blended fuels (E5, E10, and E20 and M5, M10, and M20).
When there is an increase in ethanol and methanol percentage, the CO and HC concentration decreases. The lowest CO and HC emissions are obtained with blended fuel containing methanol (M50).
Increasing the percentage of ethanol and methanol leads to a significant increase in NOx emissions.
When there is an increase in the ethanol and methanol percentage up to 30% E30 (M30), there is an increase in the NOx concentration, followed by a decrease, after which it decreases with increasing ethanol (methanol) percentage. The lowest NOx emissions are obtained with gasoline.
The present chapter has been written with the Project No 2020-RU-07’s financial assistance. We are also eternally grateful to AVL-AST, Graz, Austria, for granting the use of AVL BOOST under the university partnership program.
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