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

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.