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Optimization of PHEV/EV Battery Charging Lawrence Wang CURENT YSP Presentations RM 525 11:00-11:25 1.

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Presentation on theme: "Optimization of PHEV/EV Battery Charging Lawrence Wang CURENT YSP Presentations RM 525 11:00-11:25 1."— Presentation transcript:

1 Optimization of PHEV/EV Battery Charging Lawrence Wang CURENT YSP Presentations RM 525 11:00-11:25 1

2 Outline Background and Introduction Problem Statement and Technical Approach Battery charging system model and simulation Minimum loss algorithm formulation and test Conclusion and future work 2

3 Background EV and PHEV will help solve energy dependency and environmental issues & are becoming popular All EV/PHEV rely on batteries One of challenges is battery charging – the success of the EV will depend on availability of charging infrastructure 3

4 Battery Charger Systems On-Board Charging System Off-Board Charging System 4 Zhang et al “Research on energy efficiency of the vehicle's battery pack arch on energy efficiency of the vehicle's battery pack,” 2011 ICEICE

5 Review of Previous Charging Schemes Previous studies showed optimal charging (complex function) was very close to the CC-CV method. 5 E. Inoa, Jin Wang, “PHEV Charging Strategies for Maximized Energy Saving,” IEEE Transactions on Vehicular Technology, 2011

6 Problem Statement & Approach Problem Statement ▫Given a certain maximum time to charge a battery from a starting SOC to a final SOC, find the optimal current and voltage to minimize energy loss Approach ▫Model for both battery and charger ▫Determine total loss and charging time relationship with charging current, voltage and SOC ▫Design an method for selection of current and voltage. 6

7 Battery Model & Verification 7 Min Chen, G.A. Rincon-Mora, “Accurate electrical battery model capable of predicting runtime and I-V performance,” IEEE Transactions on Energy Conversion Battery model is modified to be consistent with the battery in the Nissan Leaf Electric Vehicle. Components are scaled by a factor of 96 cell units and a 66.2 Ah capacity. Verified to be consistent (16kWh)

8 Charger & Loss Model 8 Charging efficiency variation with current.

9 For a given SOC Vary maximum current and voltage Calculate battery and charger power loss Integrate for energy loss Matlab Model 9 End

10 Loss as Function of Current and SOC 10

11 Time as Function of Current and SOC 11

12 Voltage Relationship Loss vs. Current for 3 Maximum Voltages Time vs. Current for 3 Maximum Voltages The loss and time approaches an asymptote for higher maximum voltages. (E.g. setting a maximum voltage of 450 will yield the same result as 412.8V, as it cannot reach that voltage within the allotted time.) 12

13 Observation Raising the maximum voltage allows charging to be achieved faster, but also creates more loss at the same current. Ultimately, the decrease in time corresponds to a lower loss. There is a current that will lead to minimum loss. This current is consistent throughout all SOC. This means that for all currents below this minimum, it is better to use the threshold current. 13

14 Minimum Loss Algorithm 14

15 Implementation A neural network was developed as a function 15

16 Test in Simulation #SOC init t req (hrs)Loss (MJ)  Loss 120%0.55.1015.7% 220%1.03.5341.7% 320%8.02.9850.7% 450%0.52.1335.8% 550%1.01.7447.6% 650%8.01.7248.2% 16

17 Conclusion and Future Work A simple voltage and current selection criterion is developed in CC-CV charging mode that will result in minimal loss for a given charging time. Both battery and charger loss are considered. The algorithm tested in simulation benefits both slow and fast charging. Experimental verification will be performed in the future. 17

18 Acknowledgement CURENT faculty, staff, and graduate students 18

19 Questions 19


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