WIDE OPEN THROTTLE CONDITION USING POWER TRAIN BLOCKSETS

PROJECT NAME – WIDE OPEN THROTTLE CONDITION USING POWER TRAIN BLOCKSETS

AIM –

1. To understand the difference between mapped and dynamic model of engine, motor and generator.
2. Fuel economy – Miles per gallon and its calculation.
3. Run the HEV ReferanceApplication with WOT drive cycle. Change the grade and wind velocity in the environment block and compare the results.
4. To compare the simulated results of hybrid and pure electric powertrains.

INTRODUCTION –

PowerTrain Block Sets –

1. These are used to simulate automotive powertrain systems.
2. Powertrain blocksets provides fully assembled reference application models of automotive powertrains which includes gasoline, diesel, hybrid and electric systems. it includes components library for simulating engine subsystems, transmission assemblies, traction motors, battery packs, and controller model. Powertrains blockset also includes a dynamometer model for virtual testing.
3. This can be referred as “the library of automotive components used to construct a vehicle model” ranging of all types and applications and later used for simulation.
4. Powertrain blockset provides a standard model architecture that can be used throughout the development process. You can use it for design trade-off analysis and component sizing, control parameter optimization and hardware in the loop testing. You can customize models by parameterizing components in a reference application with your own data or by replacing the subsystem with your own model.
5. Powertrain blockset uses MATLAB & Simulink for the simulation.

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

Mapped Engine

Dynamic Engine

In Simulink we can change the model type by following the method and also using model explorer but this method is quite friendly.

Right click in the required model space, move the cursor to the variant option and then left click and then again ove the cursor to the lable mode active choice which leads to choosing the model to be active among all the models present in it and we can choose as per our choice.

Q.2) How does the model calculate Miles per Gallon? Which factors are considered to model fuel flow?

Miles per Gallon is the fuel economy rating determined by how far the car can travel on a Gallon of Gasoline or Diesel for an engine powered car.

In case of electric vehicles, this can be defined as the amount of distance travelled by engine powered car in a Gallon of a fuel and compared with the electric energy required by the electric vehicle to travel the same distance. i.e. equivalent energy required to propel the car through same distance.

The powertrain blockset has built in model for this,

According to the model following 3 factors are involved in calculating the fuel economy rating,

1. Vehicle speed.
2. Fuel flow.
3. Battery power.

1. Vehicle speed – critical criterion for evaluating the Fuel Consumption / Fuel Flow.

Vehicle speed is integrated with respect to time to obtain distance travelled later which is converted to KM units. Saturation block is used bound upper & lower limits to the obtained value.

2. Total Battery Power – it is required to propel the vehicle the vehicle is simulated along the way; battery power is converted to ‘KW’ & battery rating is obtained in terms of ‘KWh’. Several gain blocks with constant values are used to get the mass flow rate of fuel in Kg/ m³.

3. The above value is fed back as input in the Fuel Flow back, using these values along with the gain blocks fuel consumption ‘Litres’ is calculated by the results obtained from vehicle speed and fuel flow, the total amount of fuel to run vehicle for 100 Km is obtained (L/ 100 KM).

4. For evaluation of MPG – Consider the fuel flow value in m^3, and convert it into US Gal by multiplying with 264.17 in gain block and saturate the limits.

5. Simultaneously consider the distance travelled in meter and convert to miles using gain block. And now from above two values Miles/ Gallon is obtained.

Electric Vehicle -

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For Hybrid Electric Vehicle –

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Q.3) Run the HEV Reference application with WOT drive cycle. Change the grid and wind velocity in the environment block and comment on the results.

The reference HEV Powertrain Blockset is extracted from Mathworks,

Drive cycle sourceblock – generates standard or user- specified drive cycle velocity versus time profile. In this simulation we are evaluating WOT.

Environmentsubsystem – creates environment variables including road grade, wind velocity, atmosphere temperature & pressure.

Longitudinal driversubsystem – uses longitudinal driver or open loop variant to generate normalized acceleration and braking commands. Longitudinal drivevariant implements a driver model that uses vehicle target & reference velocities.

Controllersubsystem – implements powertrain control module (PCM) containing an input power-split hybrid control module (HCM) & an engine control module (ECM).

Passenger carsubsystem – implements a hybrid passenger car that contains drivetrain, electric plant, and engine subsystems.

Visualizationsubsystem – displays vehicle level performance, battery state of charge (SOC), Fuel economy, & emission results that are useful for powertrain matching and component selection analysis.

We change the drive cycle to WOT and set the parameters as –

Nominal speed – 80 Mph

Time to start deceleration – 50 Sec.

Simulation time – 100 Sec.

Wind velocity – 0 m/s.

Grade – 0.

Plot 1 – Trace & actual velocity –

We see here the trace velocity is given as input and actual velocity is the output

Top velocity achieved = 113 Mph

Time taken to attempt maximum acceleration – 19.800 sec.

Time taken to decelerate – 7.477 seconds.

Plot 2 – Engine, Motor, Generator Speed –

Maximum engine speed – 54577.57 RPM.

Maximum motor speed – 13710.66 RPM.

We see whenever the SOC falls below 70% the engine gets activated by providing torque as well as charging the battery-

Plot 3 – engine, motor, generator torque –

Maximum torque of Engine – 173 Nm.

Maximum torque Motor – 306 Nm.

Maximum torque Generator – 11 Nm.

Plot 4 – battery current –

The maximum current provided by the battery is around 512 amperes and after reaching certain point this value is constant and is the max amp. Limit of the battery.

As soon as the engine and generator gets started the battery current drops as load is shared by the engine & current goes negative because of occurrence of regenerative braking.

Plot 5 – battery SOC –

The SOC of the battery is decreased from 80% to 68% when the motor starts working, after 68% the slope of the line decreased because partial load is shared by the engine.

During this time SOC is increased because of the regenerative braking.

Because of SOC 80% to 63% in 45.509 seconds.

Plot – 6 – US fuel economy MPGe vs. Time –

Highest MPGe = 12.

Changing the parameters for WOT 2

Nominal speed – 60 Mph

Time to start deceleration – 40 Sec.

Simulation time – 100 Sec.

Wind velocity – 10 m/s.

Grade – 5.

Plot 1 – Trace & actual velocity –

We see here the trace velocity is given as input and actual velocity is the output

Top velocity achieved – 74 Mph.

Time taken to attempt maximum acceleration – 40.30 sec.

Time taken to decelerate – 4.242 sec.

Plot 2 – Engine, Motor, Generator Speed –

Maximum engine speed – 5458.56 RPM.

Maximum motor speed – 9571 RPM.

We see whenever the SOC falls below 70% the engine gets activated by providing torque as well as charging the battery-

Plot 3 – engine, motor, generator torque –

Maximum torque of Engine – 168.3 Nm.

Maximum torque Motor –287.8 Nm.

Plot 4 – battery current –

The maximum current provided by the battery is around 570 amperes and after reaching certain point this value is constant and is the max amp. Limit of the battery.

As soon as the engine and generator gets started the battery current drops as load is shared by the engine & current goes negative because of occurrence of regenerative braking.

Plot 5 – battery SOC –

The SOC of the battery is decreased from 80% to 66% when the motor starts working, after 70% the slope of the line decreased because partial load is shared by the engine.

During this time SOC is increased because of the regenerative braking.

Because of SOC 80% to 65% in 34.531 seconds.

Plot – 6 – US fuel economy MPGe vs. Time –

Highest MPGe = 9.

CONCLUSION –

1. There exists a difference between actual velocity curve and the input curve due to the limitation on maximum power available from propulsion/ energy sources.
2. Limiting factors involves current or battery module.
3. The maximum speed achieved in simulation _2 is lesser compared with simulation simulation_1 because of opposing wind force & presence of grade angle.
4. Increase in grade angle can be observed from plots.
5. WOT response time increases.
6. Velocity decreases.
7. The battery SOC also decreases considerably with the increase in traction forces.
8. Fuel economy falls to greater extent with the increase in demanding traction power.

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

Pure Electric Vehicle-

Hybrid Electric Vehicle –

SIMULATION – WOT (3) (EV)

Grade angle = 10 degrees.

Wind velocity = 15 m/s.

Total simulation time = 100 sec.

Nominal speed = 45 m/s.

Deceleration time = 40 seconds.

CONCLUSIONS –

1. 1.The pure EV drive achieves less top speed compared to HEV.
2. Motor used in EV must be of more capacity that of HEV.
3. EV drives all power from motor alone hence EV developed more torque whereas in HEV motor and engine combined produces more torque and propels the system.
4. Instantaneous torque at the start is more in EV compared to HEV.