摘要：Under the urban public transport conditions, engine operating points are lesser in the economic area. Motor operating points are scattered and its working efficiency is low. Besides, the battery state-of-charge value cannot be maintained at a certain value range. In order to solve the problems, this article uses the genetic algorithm to optimize the logic threshold control strategy and improve the fuel economy. The process of solving the objective function is attributed to the random search algorithm and is optimized by the fitness function. First, forward simulation platform of the hybrid electric bus is established by AVL CRUISE, MATLAB/Simulink, and Interface module. Second, based on the data which are collected from the actual operating conditions on the city bus, the actual operating conditions are divided into three categories: light load, middle load, and heavy load. The typical condition is selected as the simulation test condition in each case. Finally, in order to improve the fuel economy of the vehicle, the control parameters are optimized by the genetic algorithm and the optimized model is established. The main contribution of this article is the optimized energy control strategy to control hybrid electric bus’ energy distribution and reduce emissions. The strategy can be obtained by combining the logic threshold control strategy and genetic algorithm. The optimal engine torque and motor torque of the hybrid electric buses can be obtained by solving the objective function of equivalent fuel consumption. Compared to the original data model, the optimized parameter model can reduce the hybrid electric bus gas consumption, improve engine and motor efficiency, and better maintain state-of-charge values in a range under the typical operating conditions.
关键词：Hybrid electric bus; CRUISE simulation; genetic algorithm; condition identification; state of charge
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