Week-3 Challenge: ADVISOR Tool

USE OF ADVISOR TOOL FOR SIMULATION OF VEHICLES

AIM

To use Advisor Tool and Simulate the given vehicle.

OBJECTIVE

1. Concluding observations for EV_defaults_in file, can the vehicle travel for 45 km with FTP drive cycle if the vehicle carrying cargo mass of 500 kg.
2. Repeat the simulation for the same file by changing battery capacity.
3. Perform Gradeability test with the PRIUS_Ipn_defaults_in file and compare the results.

EXPLANATION

ADVISOR , NREL’s (National Renewable Energy Laboratory) advanced vehicle simulator, is a set of model, data, script text files for use with MATLAB and Simulink. ADVISOR was preliminarily written and used in November 1994. Since then, it has been modified as necessary to help manage the USE DOE Hybrid Vehicle Propulsion System Subcontracts. Only in January 1998 was a concerted development effort undertaken to clean up and document ADVISOR.

Since then, over 4500 individuals have downloaded one or more versions of ADVISOR, including all of the OEMs and major suppliers. About 2/3 of the users are from industry and 1/3 from universities. A short list of major ADVISOR users includes:

• Daimler Chrysler
• Ford Motor Company
• General Motors Corporations
• Delphi Automotive Systems
• Visteon

and hundreds of others.

It 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 drive train components, a starting point of verified vehicle data and algorithms from which to take full advantage of modeling flexibility of simulink and analytic power of MATLAB.

BENEFITS OF USING ADVISOR TOOL

• It provides the vehicle engineering community with an easy to use ,flexible yet robust and supported analysis package for advance vehicle modeling.
• It is primarily used to quantify the fuel economy, the performance, and the emission of vehicles that use alternative technologies including fuel cells, batteries, electric motors and internal combustion engines in hybrid (i.e. multiple power sources).
• It excels at quantifying the relative change that can be expected due to the implementation of technology compared to baseline scenario.
• It learns about how conventional, hybrid, or electric vehicles use energy throughout their drivetrains.
• It compares relative tailpipe emissions produced on a number of cycles.
• It evaluates an energy management strategy for your hybrid vehicle’s fuel converter.
• It optimizes the gear ratios in your transmission to minimize fuel use or maximize performance.

CAPABILITIES AND INTENDED USES

ADVISOR uses basis physics and measured component performance to model existing or future vehicles. Its real power lies in the prediction of performance of vehicles that have not yet been built. It answers the question ‘what if we build a car with certain characteristics?’

Advisor usually predicts future use, tailpipe emissions, acceleration performance, and graeability.

In general user takes two steps:

1. Define a vehicle using measured or estimated component and overall vehicle data.
2. Prescribe a speed versus time trace, along with rode grade, that the vehicle must follow.

ADVISOR then puts the vehicle through its paces, making sure it meets the cycle to the best of its abiity and measuring (or offering the opportunity to measure) just about every torque, speed, voltage, current, and power passed from one component to another.

ADVISOR will allow the user to answer questions like:

1. Was the vehicle able to follow the speed trace?
2. How much the fuel and electric energy were required in the attempt?
3. How does the state of charge of the batteries fluctuate throughout a cycle?
4. What were the peak powers delivered by the drivetrain components?
5. What was the distribution of torques and speeds that the piston engine delivered?
6. What was the average efficiency of the transmission?

By iteratively changing the vehicle defination or driving cycle the user can go on to answer questions such as

1. At what road grade can the vehicle maintain 55 mph indefinitely?
2. Whats the smallest engine I can put into this vehicle to accelerate from 0 to 60 mph in 12 sec?
3. What’s the final drive ratio that minimizes fuel use while keeping the 40 to 60 mph time below 3 sec?
4. What is the fuel economy sensitivity to mass, aerodynamic drag, or other vehicle or component variations?

ADVISORs GUI and other script files answer many of these questions automatically, while others require some custom programming on the user’s part.

Because ADVISOR is modular, its components models can be relatively easily extended and improved. For example, an electrochemical model of battery, complete with diffusion, polarization and thermal effects can easily be put into a vehicle to cooperate with a motor model that uses a measured efficiency map. Of course, developing new detailed model of drive train components requires an intimate familiarity with the environment MATLAB/Simulink.

LIMITATIONS

Primarily for analysis, not design

ADVISOR was developed as an analysis tool, and not originally intended as a detailed design tool. Its component models are quasi-static and can not be used to predict phenomenon with a time scale of less than a tenth of a second or so. Physical vibrations, electric field oscillations and other dynamics can not be captured using ADVISOR, however recent linkages with other tools such as Saber, Simplorer and Sinda/Fluint allow a detailed study of these transients in those tools with the vehicle level impacts linked back into ADVISOR.

As an analysis tool, ADVISOR takes the required /desired speed as an input, and determines what drive train torques, speeds, and powers would be required to meet that vehicle speed. Because of this flow of information back through the drive train, from tire to axle to gearbox and so on, ADVISOR is what is called a backward facing vehicle simulation.

Forward facing vehicle simulations include a model of a driver, who senses the required speed and responds with an accelerator or brake position, to which the drivetrain responds with an accelerator or brake position, to which the drivetrain responds with a torque. This type of simulation is well suited to the design of control systems, for example, down to the integrated circuit and PC card level the implementation level.

ADVISOR well suited to evaluate and by iterative evaluation, design control logic and energy management strategies. By this we mean something like ‘when the engine torque output is low and battery state of charge is high, turn off the engine.’ The control logic with which ADVISOR can work is about what you want the vehicle to do. The detailed control system, getting into details of how you would implement this control logic in hardware, is about how to make the vehicle do what you want and is not the original intension of ADVISORs application.

Power bus for electric power transfers

In electrical components communication with each other ADVISOR deals in power and not in voltage and current. Linkages to other tools, such as Saber and Simplorer let the user work with a voltage bus.

Drive axle is single only.

The vehicle dynamics calculations required for traction control and the wheel slip model assume that the front axle is the only drive axle. Simple steps can be taken to correct the weight transfer calculation if you wish to model a rear drive vehicle, and an example wheel filethat accomplishes this is included. Modeling a four wheel drive vehicle requires involved Simulink reprogramming. Please contact NREL if you have such needs.

SYSTEM REQUIREMENTS

ADVISOR has been developed and tested in release 12.1 (MATLAB 6.1 and Simulink 4.1), available from the mahworks. The mathworks software runs on multiple platform including Macintosh, UNIX, and PCs.

HOW TO GET ADDITIONAL HELP

MATLABs one line help and the Matlab and Simulink manuals can answer questions about MATLAB and Simulink functions. Type helpdesk at the MATLAB command prompt. Additionally, you can type or helpwin at the MATLAB command prompt.

Descriptions of ADVISOR block diagrams are available by opening the block diagram of interest and double clicking on the green NOTES block in bottom right or left corner. Descriptions of ADVISOR component and other files are available from the MATLAB command line by entering help ADVISOR_filename. Help is also available from within the ADVISOR GUI and subsequent chapters of this documentation.

This manual should get you started doing straightforward vehicle analysis with ADVISOR.

STEPS TO START THE ADVISOR TOOL IN MATLAB

• Download the advisor tool zip file from given sources and extract the zip file source.
• After that open Matlab and change the from current folder to where advisor tool is located.
• Then type Advisor in command window.
• Then select the unit, here we are using metric as a measuring unit then click on start button.

After clicking on the start button the vehicle input window will open so we can give inputs for modeling. Here Advisor tool have three windows:

1. Vehicle Input Window
2. Simulation Parameter Window
3. Results Window

1.Vehicle Input Window

In this we can make changes in our energy sources ,motor,weights, drive train components, load file and many other parameters. After changing required parameters we need to click on continue button then simulation parameter window will open.

2.Simulation Parameter Window

In this we can the simulation parameters of the vehicle such as drive cycle, time step, soc correction, acceleration test and gradeability test and other parameters. After clicking on RUN button the result window will appear.

3.Results Window

Here we can see various results and plots of parameters that we simulate.

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

Here we are changing our model by changing load file as EV_defaults_in file and then change cargo mass into 500 kg as per given condition and keeping other parameters as default. And now clicking on continue button we go into next simulation parameter window.

In this Simulation Parameter Window we are going to change drive cycle type i.e. CYC_FTP and number of drive cycles according to condition.

For No. of Drive Cycle = 1

Here choosing number of drive cycle 1 in simulation parameter window and then clicking on RUN button we got below results:

Distance Travelled by the vehicle is 17.8 km and the battery is still charged.

For No. of Drive Cycle = 2

Here choosing number of drive cycle 2 in simulation parameter window and then clicking on RUN button we got below results:

Here Distance Travelled by the vehicle is 35.5 km and the battery is still charged.

For No. of Drive Cycle = 3

Here choosing number of drive cycle 3 in simulation parameter window and then clicking on RUN button we got below results:

Here Distance Travelled by the vehicle is 41.4 km and the battery is all consumed.

For No. of Drive Cycle = 4

Here Distance Travelled by the vehicle is 41.4 km. After this we can not perform this simulation with number of drive cycle 4 due to insufficient battery capacity. Thus it is showing with warning messege required distance exceeded EV range.

RESULTS

Sr No	No of Drive cycles	Distance Travelled (Km)	State of Battery Charging
1	1	17.8	Charged
2	2	35.5	Charged
3	3	41.4	Consumed (Exceeded EV Range)
4	4	41.4	Consumed (Exceeded EV Range)

2] In the above simulation try to change battery capacity and repeat the simulation.

In this simulation, we are going to keep all parameters as default. and we are just going to change battery modules and observe results for different number of drive cycles.

As we increase battery mods total weight also going to change

Battery Module=26, Cargo weight = 500 kg

After changing battery mods then clicking to continue button we got simulation parameter window where we are going to select number of drive cycles.

For Drive Cycle = 1

Distance travelled by the vehicle is 17.8 km and battery is still charged more compare to previous battery as we increased battery capacity by changing battery modules.

For Drive Cycle =2

Here Distance travelled by the vehicle is 35.5 km as we increased number of drive cycle i.e. 2 and battery is still charged

For Drive Cycle = 3

Here Distance travelled by the vehicle is 42.7 km as we increased number of drive cycle i.e. 3 and battery is all consumed. Consumption of battery takes time compare to previous battery because here we increased capacity of battery (i.e. battery madule=26)

Battery Module=27, Cargo weight = 500 kg

For Drive Cycle = 1

Distance travelled by the vehicle is 17.8 km and battery is still charged more compare to previous battery as we increased battery capacity by changing battery modules.

For Drive Cycle = 2

Here Distance travelled by the vehicle is 35.5 km as we increased number of drive cycle i.e. 2 and battery is still charged

For Drive Cycle = 3

Here Distance travelled by the vehicle is 44.8 km as we increased number of drive cycle i.e. 3 and battery is all consumed. Consumption of battery takes time compare to previous battery because here we increased capacity of battery (i.e. battery madule=27)

Battery Module=28, Cargo weight = 500 kg

For Drive Cycle = 1

Distance travelled by the vehicle is 17.8 km and battery is still charged more compare to previous battery as we increased battery capacity by changing battery modules.

For Drive Cycle = 2

Here Distance travelled by the vehicle is 35.5 km as we increased number of drive cycle i.e. 2 and battery is still charged

For Drive Cycle = 3

Here Distance travelled by the vehicle is 46.3 km as we increased number of drive cycle i.e. 3 and battery is all consumed. Consumption of battery takes time compare to previous battery because here we increased capacity of battery (i.e. battery madule=28)

Finally in this condition (Battery Module =28, No of Drive Cycle =3) we succeeded to achieve required distance travelled as given in question 1.

Battery Module=29, Cargo weight = 500 kg

For Drive Cycle = 1

Distance travelled by the vehicle is 17.8 km and battery is still charged more compare to previous battery as we increased battery capacity by changing battery modules.

For Drive Cycle = 2

Here Distance travelled by the vehicle is 35.5 km as we increased number of drive cycle i.e. 2 and battery is still charged

For Drive Cycle = 3

Here Distance travelled by the vehicle is 47.7 km as we increased number of drive cycle i.e. 3 and battery is all consumed. Consumption of battery takes time compare to previous battery because here we increased capacity of battery (i.e. battery madule=29)

For this condition (Battery Module =29, No of Drive Cycle =3) we succeeded to achieve required distance travelled as given in question 1.

Battery Module=30, Cargo weight = 500 kg

For Drive Cycle = 1

Distance travelled by the vehicle is 17.8 km and battery is still charged more compare to previous battery as we increased battery capacity by changing battery modules.

For Drive Cycle = 2

Here Distance travelled by the vehicle is 35.5 km as we increased number of drive cycle i.e. 2 and battery is still charged

For Drive Cycle = 3

Here Distance travelled by the vehicle is 49.1 km as we increased number of drive cycle i.e. 3 and battery is all consumed. Consumption of battery takes time compare to previous battery because here we increased capacity of battery (i.e. battery madule=30).

For this condition (Battery Module =30, No of Drive Cycle =3) we succeeded to achieve required distance travelled as given in question 1.

RESULTS

BATTERY MODULE = 26

Sr No	No of Drive Cycle	Distance Travelled (Km)	Battery Capacity	State of Battery Charging
1	1	17.8	286	Charged
2	2	35.5	286	Charged
3	3	42.7	286	Consumed (Exceeded EV Range)

BATTERY MODULE = 27

Sr No	No of Drive Cycle	Distance Travelled (Km)	Battery Capacity	State of Battery Charging
1	1	17.8	297	Charged
2	2	35.5	297	Charged
3	3	44.8	297	Consumed (Exceeded EV Range)

BATTERY MODULE = 28

Sr No	No of Drive Cycle	Distance Travelled (Km)	Battery Capacity	State of Battery Charging
1	1	17.8	308	Charged
2	2	35.5	308	Charged
3	3	46.3	308	Charged upto 45 Km

BATTERY MODULE = 29

Sr No	No of Drive Cycle	Distance Travelled (Km)	Battery Capacity	State of Battery Charging
1	1	17.8	319	Charged
2	2	35.5	319	Charged
3	3	47.7	319	Charged upto 45 Km

BATTERY MODULE = 30

Sr No	No of Drive Cycle	Distance Travelled (Km)	Battery Capacity	State of Battery Charging
1	1	17.8	330	Charged
2	2	35.5	330	Charged
3	3	49.1	330	Charged upto 45 Km

3] Perform Gradeability test with PRIUS_Ipn_defaults_in file , compare your results and conclude.

We choose over the model as PRIUS_Jpn_defaults_in and keeping all the parameters as it is.

By clicking on the continue button we get simulation parameter window. In that clicking on Gradeability test we can adjust speed, duration and many other parameters.

For 10 sec

First case: speed = 50 mph, Duration= 10 sec

Here we are keeping the duration 10 sec and speed 50 mph of a vehicle and then checking gradeability by keeping all system enabled.

And by clicking on RUN button we got our results.

Gradeability =9.7%

Second case: speed = 55 mph, Duration= 10 sec

Gradeability =8.9%

Third case: speed = 60 mph, Duration= 10 sec

Gradeability =8.1%

For Duration 20 sec

First case: speed = 50 mph, Duration= 20 sec

Gradeability =12.4%

Second case: speed = 55 mph, Duration= 20 sec

Gradeability =11.5%

Third case: speed = 60 mph, Duration= 20 sec

Gradeability =10.6%

RESULTS

For Duration 10 sec

Sr No	Time (sec)	Speed (mph)	Gradeability
1	10	50	9.7
2	10	55	8.9
3	10	60	8.1

For Duration 20 sec

Sr No	Time (sec)	Speed (mph)	Gradeability
1	20	50	12.4
2	20	55	11.5
3	20	60	10.6

CONCLUSION

1. In EV_defaults_in vehicle input , vehicle failed to travel 45 km with CYC_FTP drive cycle. At the end of third drive cycle the maximum distance travelled by vehicle is 41.4 km and battery is all consumed. Here we can conclude that as number of drive cycle increases, distance travelled by the vehicle also increases and ctate of battery charge decreases.
2. To cover 45 km we can use 28 modules 345 volt battery or 29 modules 358 volt battery or 30 modules 370 volt battery. By adding the battery modules battery voltage capacity increased and we can achieve required distance before battery gets consumed.
3. In third question we can conclude that as vehicle speed increases, gradeability decreases and as time duration increases, gradeability increases.