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A Dual Distribution Control Method for Multi-Power Components Energy Output of 4WD Electric Vehicles
Zhiqi Guo1, Liang Chu1, Zhuoran Hou1
1State Key Laboratory of Automotive Simulation and Control, Jilin University, No. 5988, Renmin Street, Nanguan District, Changchun 130022, China.
Sensors (Basel, Switzerland)
|December 23, 2022
Summary
This study introduces a dual equivalent consumption minimization strategy (D-ECMS) for four-wheel drive electric vehicles (4WD EVs). D-ECMS enhances vehicle economy and driving range by optimizing power component operation during driving and braking.
Area of Science:
- Automotive Engineering
- Electric Vehicle Technology
- Control Systems
Background:
- Effective energy management is crucial for optimizing the efficiency of four-wheel drive electric vehicles (4WD EVs).
- Coordinated control of multiple power components is essential for both driving and regenerative braking in 4WD EVs.
Purpose of the Study:
- To propose and validate a novel Dual Equivalent Consumption Minimization Strategy (D-ECMS) for improving the energy economy of 4WD EVs.
- To enhance vehicle performance and extend driving range by optimizing power component operation.
Main Methods:
- Development of a D-ECMS algorithm for proportional control of multi-power components based on vehicle states (driving/braking).
- Simulation of the 4WD EV using MATLAB/Simulink to evaluate the D-ECMS performance.
- Comparison of D-ECMS with a rule-based strategy.
Main Results:
- The D-ECMS effectively distributes energy output among power components, optimizing their operating points within high-efficiency ranges.
- Vehicle dynamic performance requirements were met while improving overall economy.
- A 4.35% increase in economy was observed with D-ECMS compared to the rule-based strategy.
Conclusions:
- The proposed D-ECMS offers a significant improvement in the energy economy of 4WD EVs.
- This strategy optimizes power component utilization for enhanced efficiency and extended driving range.
- D-ECMS provides a viable solution for advanced energy management in electric vehicles.
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