Simulating Electric Vehicles for Range, gradebility and performing parametric study using ADVISOR tool in matlab.

AIM : Simulating Electric Vehicles for Range, gradebility and performing parametric study using ADVISOR tool in matlab.

ADVISOR (ADvanced VehIcle SimulatOR) :

ADVISOR, NREL’s ADvanced VehIcle SimulatOR, is a set of model, data and script text files for use with Matlab and Simulink. It is designed for rapid analysis of the performance and fuel economy of conventional, electric, and hybrid vehicles. ADVISOR also provides a backbone for the detailed simulation and analysis of user defined drivetrain components, a starting point of verified vehicle data and algorithms from which to take full advantage of the modeling flexibility of Simulink and analytic power of MATLAB.

Benefits of Advisor are :-

• Estimate the fuel economy of vehicles that have not yet been built.
• Learn about how conventional, hybrid or electric vehicles use (and lose) energy throughout their drivetrains.
• Compare relative tailpipe emissions produced on a number of cycles.
• Optimize the gear ratios in your transmission to minimize fuel use or maximize performance, etc.

The models in ADVISOR are :-

• mostly empirical, relying on drivetrain component input/output relationships measured in the laboratory, and quasi-static, using data collected in steady state (for example, constant torque and speed) tests and correcting them for transient effects such as the rotational inertia of drivetrain components.

OBJECTIVE :

1. For EV_defaults_in file, if cargo mass is 500 kg with all other default conditions, can the vehicle travel for 45 km with FTP drive cycle? Conclude observations.

2. In the above case, try changing the battery capacity and repeat the simulation.

3. Perform gradeability test with PRIUS_Jpn_defaults_in file

   Compare results in table and conclude.

STUDY - 1 :

Vehicle Input :

Considering the case for an typical EV, lets simulate EV_defaults_in, an electric vehicle with following specifications :-

Enery storage : Lead Acid battery with 25 modules having 308 V as nominal voltage with 0.92 motor efficiency.

Motor : AC induction motor with 75kW

Transmission : Manual

Drive : Front wheel drive

Cargo Mass : 500kg

Simulation Parameters :

• Here, we input the drive cycle called CYC_FTP which is 17.7 km long in distance. Hence inorder to drain the battery completely to SOC = 0% for calculating the range of vehicle, 4 drive cycles are repeated, so that vehicle will travel 70.8 km in total and we can find out at what distance the SOC is 0.

Result For Input Cycle - 1 :

• In the above figure, first plot shows the drive cycle for which vehicle has travelled, the second plot shows th SOC fall with time, the third and the fourth graph show th power output according to the throttle condition.

Result For Input Cycle - 3 :

• Hence, after running the simulation, we can see that, the SOC becomes zero after aproximately 2.5 drive cycles. As shown at the right hand side, the distance travelled by vehicle is 41.4 km.

CONCLUSION :

• From the above simulation we can observe that the vehicle does not travel 45 km with the FTP drive cycle for the default conditions.
• In order to increase the distance travel by the vehicle, the number of battery modules should be increased.

STUDY - 2 :

Vehicle Input :

Considering the case for an typical EV, lets simulate EV_defaults_in, an electric vehicle with following specifications :-

Enery storage : Lead Acid battery with 27 modules having 333 V as nominal voltage with 0.92 motor efficiency.

Motor : AC induction motor with 75kW

Transmission : Manual

Drive : Front wheel drive

Cargo Mass : 500kg

Simulation Parameters :

• After continue, we run the simulation for 4 cycles so that to get the maximum distance, which can be traveled by this vehicle on this battery capacity.

Result For Input Cycle - 1 :

• By keeping all the other things at default now running the simulation. The above figure shows the distance traveled by the vehicle with 27 battery modules.

Result For Input Cycle - 4 :

• In the above image, the vehcile travels a distance of 45 km. Hence 27 number of battery modules are sufficient to satisfy a range of 45km according the problem description.

CONCLUSION : From the above graph of SOC it is evident that the State of Charge at 0 % after completing 4 FTP Drive cycles. Also under the Fuel Consumption tab, the distance travelled is displayed 45 km, unlike the previous case where the distance travelled was 41.4 km. Hence by increasing the number of battery modules from 25 to 27, we could make the EV car easily travel for 45 km.

STUDY - 3 :

Vehicle Input :

The above figure shows the PRIUS_Jpn_defaults_in configuration with all the default conditions and Specifications :-

Power produced by IC engine : 43kW with fuel convertor efficiency of 0.39

Battery Capacity : NMH(Nickel Metal Hydride) batteries have been used with 40 modules producing a nominal voltage of 308V

Generator(Regenerative) : 15kW

Motor :Induction motor producing power of 15kW with 0.84 efficiency.

Transmission : CVT

Drive : Front wheel drive

Simulation Parameters with Grade Test Options :

• Inorder to perform the gradeability test. We keep the grade value constant and change the speed values to find out the maximum gradeability at an optimum speed simulating for 10s.

Result :

Following are the output results for different speeds :

Case 1 : Speed = 25 mph

Case 2 : Speed = 55 mph

Case 3 : Speed = 85 mph

Table Of Output Results :

Sr. No.	Speed (mph)	Speed (kmph)	Gradeability (%)
1	25	40.2	16.5
2	35	56.3	13
3	45	72.4	10.7
4	55	88.5	8.9
5	65	104.6	7.2
6	75	120.7	5.3
7	85	136.8	3.6

CONCLUSION : From the above table it is seen that the Gradeability has been tested for different Speed values keeping the Duration values as constant. From the table it is evident that the Gradeability decreases with the increase in Speed of the vehicle. The change in Duration has no effect on the Gradeability of the vehicle.