-- Siemens-Autonomie to simulate a model base design of midsize series hybrid electric vehicle
-- Used FTP 75, HWFET and UDDS cycles to measure and record vehicle performance.
1. Component Sizing of
Plugin Hybrid Electric
Vehicle for Sub-Optimal
Fuel Efficiency and
emissions
Submitted By:
Mohit Suri
2. Plug-In Hybrid Electric
Vehicle
Has an External Port for charging the
Vehicle.
Can be charged from wall socket.
During Starting, if SOC is low external
power source may charge the battery
instead of engine.
Can have an On- board Charger to
increase the range.
Two types-Parallel and Series.
4. Autonomie - A simulation
tool
Autonomie is a Plug-and-Play Vehicle
Model Architecture and Development
Environment.
Math-based simulation environment.
Autonomie is an open architecture to
support the rapid integration and analysis
of powertrain/propulsion systems.
The software has been developed by
Argonne labs
6. Strategy and Cost function
Initially Particle Swarm Optimization was proposed to
be used.
Used Trail and Error technique to successfully
optimize the Cost function.
The Cost Function here is Improving Fuel Economy
and reduce 𝐶𝑂2 emissions.
Cost Function =min
X→Ω
F(X) , X = [𝑃𝑚, 𝑃𝑒, 𝑁𝑏𝑚, 𝐶𝑓] 𝑇
Where, Nbm = number of battery modules
Cf = fuel consumption
Pm = Motor Power
Pe = Engine Power
9. Sizing Engine
Initially Engine size was to deliver
57KW of the power.
Values of the Engine power were varied
between 60 and 46 KW.
Simulation Showed that 48KW gave the
best fuel Economy.
Engine Size with 48KW was taken as
optimized result on basis of Trial and
Error.
12. Sizing the Motor
Traction Motor plays a vital role in
improving the fuel economy of vehicle.
Size of traction Motor was varied from
45 KW to 60KW.
Motor with 52 KW came out to be the
best size for best fuel economy.
Similarly Motor 2 Size was varied from
30 to 45 KW with best size being 33KW.
15. Sizing the Battery
Battery Series parallel Configuration
was changed to get optimized Results.
The Series/parallel cell configuration
was tried and results were obtained.
Battery power of 5.8KWh was optimum.
SOC Vs Time
16. Changing Kp and Ki
Kp and Ki Are the controller gains.
Individual parametric study was done.
Best values were selected to get
optimum values.