2. Energy Optimization in Electric Vehicles
Dr. Kumeresan A. Danapalasingam
Department of Control & Mechatronics Eng.
Faculty of Electrical Engineering
Universiti Teknologi Malaysia

3. Electric Vehicles
Why energy optimization in an EV?

4. Electric Vehicles Electric Vehicles
Hybrid Electric Vehicles (HEVs)
Plug-in Hybrid Electric Vehicles (PHEVS)
All-Electric Vehicles (EVs)

5. Electric Vehicles Powered by an Electric Motor Driving Range
Battery stores electrical energy that powers the motor
Battery charged by plugging into outside electric power source
Zero tailpipe emissions, but air pollution may be produced through electricity generation
All-Electric Vehicles (EVs)
Driving Range
EVs can travel km per charge, depending on the model.
A 160-km range is sufficient for more than 90% of all U.S. household vehicle trips.

6. Electric Vehicles
To keep EVs running, they need to be charged
Level 1: 120 V, alternating current (AC) plug; dedicated circuit, full charge takes 8-20 hours
Level 2: 240 V, AC plug and uses the same connector on the vehicle as Level 1, full charge takes 3-8 hours
Level 3: In development; faster AC charging, full charge could take less than 30 minutes
DC Fast Charging: Equipment (480 V) provides 50 kW to the battery and can take less than 30 minutes to fully charge a battery
Inductive Charging: Installed for early EVs and is still in use in certain areas—possible method of charging for future EVs

7. Save electrical energy
Electric Vehicles
Save electrical energy
Save cost
Save environment
Increase range
Save time

8. Electric Power Steering
Subsystems in an EV
VCM
Entertainment, Lighting, Radiator Fan, Display Panel, door, safety unit, wiper, etc
DISPLAY
BECU
Research focus
AUX
BMCU
SAT-NAV
MCU
Brake Vacuum Pump
EPSU
E-ACU
OBCU
DC-DC Converter
WPU
HV Battery
Traction Motor
Electric Power Steering AC
On-Board Charger
E-Water Pump
PROPULSION LOAD
NON-PROPULSION LOAD

9. Stage 1 – Non-propulsion load
Title: Energy Optimization of Electric Power-Assisted Steering System
Abstract
Electric power-assisted steering (EPS) is a control system where an electric motor is used to provide assistance in vehicle steering.
In this work controllers are designed for a column-type EPS equipped with brushed DC and brushless DC (BLDC) motors to enable energy optimization.
Using a mathematical model of EPS a controller is developed based on nonlinear adaptive regulation method to generate driver torque.
PID control is then applied to produce assistance torque in accordance to desired energy saving.
Simulation results using Matlab show the trade-off between driver’s comfort and energy consumption.
The control paradigm introduced here fits appropriately in electric vehicles (EVs) where electrical energy is scarce.

10. Stage 1 – Non-propulsion load
Proposed features:
Motor
brushed DC motor
brushless DC motor
Nonlinear tire-road dynamics and friction
To produce simulation results that
reflect real world scenario
To design a feasible controller
Nonlinear controller
To be able to achieve control objectives
in a robustly stabilizing manner
Energy optimization
Eco factor, E

11. Stage 1 – Non-propulsion load
Mathematical model:

12. Stage 1 – Non-propulsion load

13. Stage 1 – Non-propulsion load
List of symbols:

14. Stage 1 – Non-propulsion load
Results – Brushed DC

15. Stage 1 – Non-propulsion load
Results – Brushed DC

16. Stage 2 – Propulsion load
Title: Electric Vehicle Traction Control for Energy Optimization
Abstract
An electric vehicle (EV) with four in-wheel motors offers several advantages over other types of EVs.
Due to a limited electrical energy source and a long battery charging time, any ways to minimize energy consumption in an EV has to be fully utilized.
Undoubtedly one of the systems in an EV that drains the most amount of energy is the propulsion system.
In this work the existence of an optimal slip ratio that enables energy saving in an EV propulsion system is investigated.
A controller is designed to ensure the slip ratio of each wheel is limited by the optimal value.
Simulation results demonstrate the effectiveness of the proposed traction control scheme in energy optimization in an EV.

17. Stage 2 – Propulsion load

18. Stage 2 – Propulsion load
Vehicle Dynamics
Mathematical model:

19. Stage 2 – Propulsion load
Driver Controller

20. Stage 2 – Propulsion load
Driver Controller
Hard suspension

21. Stage 2 – Propulsion load
Driver Controller
Soft suspension

22. Stage 2 – Propulsion load
Optimal Slip Ratio

23. Stage 2 – Propulsion load
Simulation Results

24. Stage 2 – Propulsion load
Simulation Results

25. Stage 2 – Propulsion load
Simulation Results

26. Conclusion Conclusion
Electrical energy optimization for a non-propulsion load (EPS) and a propulsion load (propulsion system) are considered.
Conventional method of determining target assist motor current using a lookup table is completely eliminated to give way to an approach enabling battery energy saving.
Rather that using fixed values of reference assist motor current to generate required assistance torque here an option is enabled to set the level of steering comfort as desired, by means of the eco factor E.
For the propulsion load the existence of an optimal value of slip ratio of each wheel of a four-wheel drive electric vehicle (EV) with in-wheel motors is shown.
Since exceeding the optimal slip ratio only results in a reduction of longitudinal tire force, it is considered as a waste of the electrical energy.
A controller is developed to keep the slip ratio of each wheel below the optimal value.

27. Thank You