Equivalent consumption minimization strategy of hybrid electric vehicle considering the impact of driving style

Abstract

The impact of driving style on the fuel economy is normally unconsidered in the development process of the equivalent consumption minimization strategy for hybrid electric vehicles. This article established a real vehicle energy management strategy based on the combination of driving style recognition and optimized equivalent consumption minimization strategy. In detail, the driving style recognition algorithm is obtained by introducing the driving style identification coefficient containing driving condition type influence factor and combining the coefficient with the genetic optimization K-means driving condition recognition algorithm. The equivalent consumption minimization strategy is optimized by genetic algorithm to optimize the battery SOC penalty function and charge–discharge coefficient. Comparing the proposed energy management strategy with the traditional equivalent consumption minimization strategy in a stochastic driving condition, the simulated result shows that the fuel consumption rate is reduced by 8.49% by making the operating points of the engine closer to the engine best efficiency curve, and making battery SOC changes more smooth and maintaining it in a reasonable area. It means that the proposed energy management strategy achieves higher fuel computation efficiency and better power distribution between the integrated starter generator and the engine.