Week-4 Challenge WOT Condition Part-2

Aim:To study on Powertrain Blockset in MATLAB

SOLUTION1:

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

Powertrrain Blockset provedes two types of engine models:mapped and dynamic.Mapped engines represent macro engine behaviour as a set of lookup tables (brake torque,fuel flow,air mass flow,exaust temparature,efficiency,and emissions)as functions of commanded load and measured engine decompose engine behaiour  into individual component models that account for engine dynamics,most notably intake airflow and turbochanger dynamics.

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

MAPPED MODEL:

1)It uses a prebuilt data in lookup table for the simulation of powertrain block set.

2)In Mapped model the calculations are very fast.

3)Elecric losses are need to be specified if present.

DYNAMIC MODEL:

1)It uses real timedata for calculating every behaviour of vehicle characterstic like speed,velocity,drag,wheel braking etc.

2)In dynamic model the calculations are time consuming.

B)Changing Model Type:

1)Open EV Reference Application in powertrain blockset of MATLAB as shown in figure below.

Note:For results open visualisation

2)Now open the passenger car block and select the Electric plant block as shown in figure.

3)Then select the MotGenEVMapped block as shown below .

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

5)Now for changing mapped to dynamic blockset,right click on the screen and select variant.Then select Labell mode Active choice and select MOtGenEvDynamic.

6)Similarly we can change from 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 of 2474 sec is shown below.the result graph is obtained in visualisation block.

SOLUTION 2:

MILES PER GALLON(MPG) is a fuel economy rating determined by how far a car can travel on a gallon of gasoline or diesel.Although the metric version would be kilometer per liter,MPG is adopted in many metric-system countries,like canada

   While it is both cheaper and better for the environment to achieve a higher MPG rating,that the EPA calls  the 'MPG illusion.that shows the cost benefits of increasing MPG decreases with higher rating.For  ex to travel 1000 miles a car that gets 10 MPG wiil require 100 gallons of fuel.converesely a car that gets 15MPG 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,incresing its mileage of 30 MPG ,however  increasing its mileage  to 35 MPG will only save 5 gallons of fuel over 1000 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 done in liters per 100 kilometers (L/100km),and in the USA,this is done in gallons per 10 miles (gal/100ml).

CALCULATION OF MILES PER GALLON IN 'EV REFERENCE APPLICATION MODEL:

1)Open EV reference 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 

Note:264.172 US Gallons = 1000L

1 Gallon=33.7 kilowatt hours of Energy in electrical 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 miles)then it is divided by Gal to get MPG.

4)For US Gallon we need divide battery power divided by 1000 and then divide by 33.7.Now it is converted from sec to hours by dividing with 3600 then it is converted to m^3 per gal.

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

FACTORS CONSIDERED IN MODEL FUEL FLOW:

1)Battery power capacity should be high and vehicle power coonsumption should be low for higher MPG(miles per gallon equivalent).

2)vehicle speed.

SOLUTION 3:'HEV REFERENCE APPLICATION WITH WOT DRIVE CYCLE.

Introduction:The hybrid electric vehicle reference application represents a full multimode hybrid electric vehicle(HEV)MODEL with internel combusion engine.

Transmission,battery ,motor ,generator,and associated powertrain control algorithms.Use the reference application for powertrain matching analysis and diagostic algorithm design,and hardware-in-the-loop(HIL)testing.

BY DEFAULT THE HEV MULTIMODE REFERENCE APPLICATION IS CONFIGURED WITH:

1)Mappped motor and generator

2)1.5-L spark-ignition(SI)Dynamic engine

HEV Reference Application model:

Description:

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

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

case1:

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

RESULT:

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

2)Engine speed is able to achieve 8000 RPM and battery state of cahrge(SOC)was decreses from 80to72.

3)Engine torque increases initially and goes to negative after 20th second and the peak torque achieve was around 275Nm.The fuel economy was increased from 0to16 and remain constant.

CASE2:

Now changing the Environmen sub-system in case 1 specification of HEV reference application the grade was now changed from  0 to 8 and wind velocity from 0 to 4.

RESULT:

1)The target velocity actual was only able to achieve 50.4mph.The battery current was increased upto 500 amp and maintained for a duration of 14 sec.

2)Engine speed was able to achieve 8000rpm but for a small duration of time and battery state of charge(SOC)was decrease from 80to 70.

3)Engine torque increases initially and goes to negative after 20th second and the peak torque achieve was around 275 Nm.The fuel economy was increased fro 0 to 8.7 and remains constant.

SOLUTION 4:

CASE 1:HEV Multimode Reference Application

1)open Hev Reference Application model in MATLAB.

2)tHE model consist of Environment,Drive cycle Longitudinal Driver.

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

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

CASE 2:EV REFERENCE APPLICATION MODEL:

1)open Electric Vehicle Reference Application model in MATLAB.

2)The model consist of environment, Drive cycle,Longitudinal Driver passenger and vixualisation subsystem as similar to HEV but as it i apure elecrtric vehicle the complexity in the model is less and the rendering time is less.

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

4)Now run the simulation with 2474sec and go to visualisation to see

CONCLUSION:

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

2)The US fuel economy is high in EV compared to HEV,travellingcost is less forEV.

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