Challenge

Week-3 Challenge: ADVISOR Tool

SSoumya R Pradhan21 Dec 2022

AIM: To simulate the given data and conditions for an EV using Advisor Tool in MATLAB.

Objective:

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

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

3. To Perform gradeability test with PRIUS_Jpn_defaults_in file. To compare results in the table and conclude.

Introduction

ADVISOR tool, developed in November 1994 by the National Renewable Energy Laboratory (NREL), allows users to simulate and analyze conventional, advanced, light, and heavy vehicles, including hybrid electric and fuel cell vehicles.

theory

What is ADVISOR TOOL ;

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 economyconventional,

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.

benifit;

* 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

* mostly empirical, relying on drivetrain component input/output relationships measured in the laboratory. * 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.

* Compare relative tailpipe emissions produced on a number of cycles

* Evaluate an energy management strategy for your hybrid vehicle’s fuel converter

* Optimize the gear ratios in your transmission to minimize fuel use or maximize performance, etc.

using advisor;

* Launch MATLAB and first set default location folder to the advisor.

* Now in the command window of MATLAB type “advisor” and press enter.

* A new window will open and then set “metric” for unit and start ADVISOR.

* It will launch in a new window.

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 your observations.

ans

First, loading EV_defaults_in from the drop-down menu and changing Parallel_default_in to EV_defaults_in from Vehicle Input window.

* Now changing the cargo mass to 500 kg

* Change in the total mass of the vehicle can be seen.

* Clicking on the continue button after that a new window simulation parameter will pop up.

LOAD FILE: EV_defaults_in ; CARGO MASS: 500KG

DRIVE CYCLE: CYC_FTP ; NO. OF CYCLES: 1

Result;

The distance traveled by the vehicle in 1 drive cycle is 17.8km. Used almost 40% SOC

DRIVE CYCLE: CYC_FTP ; NO. OF CYCLES: 2

Result;

The distance traveled by the vehicle in 2 drive cycles is 35.5km. Used almost 81% SOC.

DRIVE CYCLE: CYC_FTP ; NO. OF CYCLES: 3

Result;

The distance traveled by the vehicle in 3 drive cycles is 41.4km. Used completely 100% SOC.

CONCLUSION: Thus we can see that for 3 number of cycles at the given conditions,the vehicle can travel for only 41.4km

If we increase the number of cycles,then the vehicle can travel above 45km.

Q2. In the above case, try changing the battery capacity and repeat the simulation.

ans:

* In-Vehicle Input window we will change the capacity of battery form energy storage which will be open in 1^st

* describes the battery capacity, so we will change the module number of batteries from the first box and we will see that changes in voltage and weight of the battery.

* A new Simulation Parameter window will open, here we will change the drive cycle to 3 one at the time and run the simulation.

* After completing of simulation, we will see the result window where we observe the change in distance of vehicle travel.

* We can repeat this simulation by changing the battery module and the drive cycle.

i) Energy Storage System with 27 modules and 3 drive cycles.

Result:

ii) Energy Storage System with 28 modules and 3 drive cycles.

Result:

iii) Energy Storage System with 29 modules and 3 drive cycles.

Result:

Drive cycle - 3

Battery mode Voltage Km Battery weight

27 333 44.8 297

28 345 46.3 308

29 358 47.7 319

* Changing the battery module in drive cycle 3 we get changes in distance travel by vehicle.

* To cover 45km distance a 28 module 345-volt battery & 29 module 358-volt is required.

Battery modules 28 & 29 with 3 drive cycles, the distance traveled is 46.3km or 47.7 km .

3. Perform gradeability test with PRIUS_Jpn_defaults_in file

Compare your results in table and conclude.

ans:

* In ADVISOR tool Vehicle Input window select PRIUS_Jpn_default model.

* Continue to the next window.

* Simulation Parameter window will open.

* Select the gradeability test and click on the grade Option box, a new dialogue box will open.

* In grade option box we can change speed or duration with respect to our simulation.

* So, for this simulation, I change speed one time and duration another time.

* Click on All system enabled.

* Also, click on constant road grade.

* Click Ok and run the simulation and a Result window will open showing different results depend upon input data.

Results for the duration - 15sec

i) Speed - 30 miles/h or 48.3 kmph

Gradeability = 16.9%

Results for the duration - 15sec

i) Speed - 40 miles/h or 64.4 kmph

Gradeability = 13.8%

Results for the duration - 15sec

i) Speed - 50 miles/h or 80.5 kmph

Gradeability = 11.6%

Results for the duration - 15sec

i) Speed - 60 miles/h or 96.6kmph

Gradeability = 9.9%

Results for the duration - 15sec

i) Speed - 70 miles/h or 112.7 kmph

Gradeability = 7.7%

For duration - 15sec

s.l no vehicle speed mph vehicle speed kmp gradebility%

1 30 48.3 16.9

2 40 64.4 13.8

3 50 80.5 11.6

4 60 96.6 9.9

5 70 112.7 7.7