Litcius/Paper detail

Parameter optimization of rule-based control strategy for multi-mode hybrid electric vehicle

Du Wei, Shengdun Zhao, Liying Jin, Jingzhou Gao, Hao Li

2020Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering24 citationsDOI

Abstract

Multi-mode hybrid electric vehicle is considered as the best hybrid power solution because it has many operational modes and can achieve a wider and more efficient transmission range. But at the same time, it also brings some problems, such as the choice of operational mode. At present, the most commonly used mode-switching strategy is rule-based control strategy, but it needs to determine the logical threshold value of each control variable in advance. Usually these values are determined by experience, but cannot guarantee that the value obtained is the optimal solution. This paper combines the improved NSGA_II algorithm with the rule-based control strategy and optimizes the logic threshold value by using the improved NSGA_II algorithm to get the optimal logic threshold value. Combining the optimized rule-based control strategy with the minimum equivalent fuel consumption strategy, a real-time control strategy for multi-mode hybrid electric vehicle is proposed. The advantages of the proposed control strategy are proved by an example.

Topics & Concepts

Mode (computer interface)Range (aeronautics)Control (management)Computer scienceRule-based systemFuel efficiencyElectric vehicleTransmission (telecommunications)Control theory (sociology)Continuously variable transmissionMathematical optimizationPower (physics)EngineeringAutomotive engineeringMathematicsArtificial intelligenceQuantum mechanicsPhysicsTelecommunicationsOperating systemAerospace engineeringElectric and Hybrid Vehicle TechnologiesAdvanced Battery Technologies ResearchElectric Vehicles and Infrastructure
Parameter optimization of rule-based control strategy for multi-mode hybrid electric vehicle | Litcius