Week-4 Challenge WOT Condition Part-2

Aim:- To study on Powertrain Blockset in MATLAB.

Objective:-

1) What is the difference between mapped and dynamic model of engine, motor and generator? How can you change model type?

2) How does the model calculate miles per gallon? Which factors are considered to model fuel flow?

3) Run the HEV Reference Application with WOT drive cycle. Change the grade and wind velocity in the environment block. Comment on the results.

4) Keeping all other parameters same, compare the simulated results of hybrid and pure electric powertrains.

Solution 1:-

A) Difference between mapped and dynamic model of engine, motor and generator.

        Powertrain Blockset provides two types of engine models: mapped and dynamic. Mapped engines represent macro engine behavior as a set of lookup tables (brake torque, fuel flow, air mass flow, exhaust temperature, efficiency, and emissions) as functions of commanded load and measured engine speed. Dynamic engines decompose engine behavior into individual component model that account for engine dynamic, most notably intake airflow and turbocharger dynamics.

        You can switch netween engine model types based on your application. Dynamic engine models are suitable for designing control, estimator, and diagnostic algorithms that depend on dynamic subsystem states, for example, in closed-loop AFR control algorithm development. Mapped engine models are sutable for analysis and design activities that do not require engine subsystem dynamic characteristics, for example, in engine and transmission powertrain matching analysis for fuel economy, emissions, and performance tradeoffs.

Mapped Model:-

• It uses a prebuit in lookup table for the simulation of powertrain block set.
• In mapped model the calculations are very fast.
• Electric losses are need to be specified if present.

Dynamic Model:-

• It uses real time data for calculating every behavior of vehicle characteristic like speed, velocity, drag, wheel braking etc.
• In dynamic model the calculations are time consuming.

B) Changing Model Type:-

       Open 'EV Reference Application' in Powertrain blockset of MATLAB as shown in figure below. It is a Simulink in model which consists of Drive cycle. Environment conditions, Longitudinal Driver controllers and Passenger Car.

NOTE:- For results open visualisation.

Now open the passenger car Block and select the Electric plant block as shown in the figure below.

 

Then select the 'MotGenEVMapped' blocked as shown below.

From the below figure it is clear that by default mapped motor is selected.

Now for changing mapped to dynamic blockset, right click on the screen and select variant. The select label Mde Active choice and select MotGenEVDynamic.

Similarly we can change for dynamic to mapped by selecting MotGenMapped option.

Results:- By clicking on Run the results obtained when FTP75 drive cycle is used with a simulation time 2474 sec is ahwon below, the result graph is obtained in visualization block.

Solution 2:-

                Miles per gallon (MPG) is a fuel economy rating determined by how a car cab travel on a gallon or diesel. Although the metric version would be kilometres per litre. MPG is adopted in many metric-system countries, like canada.

While it is both cheaper and better for the environvirent to achieve a higher MPG rating, there is a curve, that the EPA calls the "MPG illusion" that shows the cost-benefits of increasing, MPG decrease with higher rating. For example, to travel 1,000 miles, a car that gets 10 MPG will require 100 gallons of fuel. Conversely, a car that gets 15 MPG will require 67 gallons of fuel. In this case, an increase of just 5 MPG cuts fuel consumption by 33%. When a car gets 30 MPG, however, increasing its mileage to 35 MPG will only save 5 gallons of fuel over 1,000 miles.

Because of this 'MPG Illusion,' car makers in both the United States and Canada are beginning to list their cars' mileage in fuel consumption per distance. In Canada, this is done in liters per 100 Kilometers (L/100km), and in the USA, this is done in gallon 100 miles (GAL/100mi).

 

Miles that one gallon can provide

Because of this "MPG Illusion," car makers in both the United Sates and Canada are beginning to list their cars' mileage in fuel consumption per distance. In Canada, this done in liters per 100 kilometers (L/100km), and in the USA, this is done in gallons per 100 miles (gal/100mi).

From the above data it is clear that the fuel economy (MPG) is high in Electric vehicles.

Calculation of miles per gallon in 'EV Reference Application' model:-

1) Open Everference application model in MATLAB and inside the visualisation block we can see the blocks which are used for calculation of MPG.

2) Now open the performance calculation block as shown below figure.

Note:-

• 264.172 US Gallons = 1000L
• 1 Gallon = 33.7 Kilpwatt hours of Energy in electric vehicles.

3) Here vehicle speed (X) is multiplied itself and then square rooted. The value is then integrated (1/s) and converted into meters(m). Then the meters(m) is converted into miles in the block (m to mile) then it is divided by US Gal to get US MPG.

4) For US Gallon we need to divide battery power divided by 1000 and then divide by 33.7. Now it is converted frin sec ti hours by dividing with 36000 then it is converted to m^3 per gal.

5) The value is finally converted into Gallon and used as MPG after dividing miles with gallon.

Factors considered in model fuel flow:-

1) Battery power Capacity should be high and vehicle power consumption should be low for higher MPGe (Mile Per Gallon equivalent).

2) Vehicle speed.

Solution 3:- 'HEV Reference Application' with WOT drive cycle.

Introduction:-

The hybrid electric vehicle reference application represents a fully multimode hybrid electric vehicle (HEV) model with an internal combustion engine, transmission, battery, motor, generator, and associated powertrain control algorithms. Use the reference application for powertrain matching analysis and complaint selection, control and diagnostic algorithm design, and hardware-in-the-loop (HIL) testing.

By default, the HEV multimode reference application is configured with

• Mapped motor and generator
• 1.5-L spark-ignition (SI) dynamic engine

This diagram shows the powertrain configuration.

HEV Reference Application model:-

Description:-

1) Open 'HEV Reference Application' model in MATLAB.

2) It consist of various subsystems which are similar to 'EV Reference Application' but the complexity is more in'HEV Regerence Application' model.

Case 1:-

The default drive cycle is FTP75 with 2474 sec. Now change it to WOT drive cycle as below with WOT simulation time as 180 and click on 'OK'.

Result :-

1) The target velocity actual was able to achieve 67.1 mph. The battery current was increased upto 500 Amp and maintained for a duration of 14 sec.

2) Engine speed is able to achieve 8000 RPM and battery State of Change (SOC) was decrease form 80 to 72

3) Engine torque increases intially and goes to negative after 20th second and the peak torque achieve was around 275 Nm. The fuel economy was increased from 0 to 16 and remains constant.

Graph 1:-

Case 2:-

Now changing the Environment sub-system in case1 specification of 'HEV reference application. The grade was now changed for 0 to 16 and wind velocity from 0 to 4

Graph:-

Result:-

1) The target velocity actual was only able to achieve 50.4 mph. The battery current was increased upto 500 Amp and maintained for a duration of

14 sec.

2) Engine speed was able to achieve 8000 RPM but for a small duration of time and battery State of Charge(SOC) was decrease from 80 to 70

3) Engine tonque increases initually and goes to negative after 20th second and the peaktorque achieve was around 275 Nm. The fule economy was increased rom 0 8.7 and remains constant.

Solution 4:-

Case 1:- HEV Multimode Reference Appliation

1) Open Hev Reference Application model in MATLAB.

2) The model consist of Environment, Drive cycle, Longitudinal Driver passenger and visualisation Subsystem.

3) Open the environment block and change the grade value to 7 and wind velocity to 5.

4) Now run the simulation with 2474 seconds and go to visualisation to see the graph.

Model:-

Result graph :-

Case 2 :- EV Reference application model

1) Open electrical vehicle reference application model in MATLAB.

2) The model consist of Environment, Drive cycle, Longitudinal Driver passenger and visualisation Subsystem as similar as HEV but as it is a pure electrical vehicle the complexity in the model is less and rendering time is less.

3) Open the environment block and change the grade value to 7 and wind velocity to 5.

4) Now run the simulation with 2474 seconds and go to visualisation to see the graph.

Model:-

Result Graph :-

Conclusion:-

1) Battery current is continously changing in HEV due to charging and discharging while in pure EV the battery current is consistently dropping.

2) The US fuel economy is high in EV compared to HEV, travelling cost is less for EV.

3) The motor speed(RPM) is high for HEV compared to EV.