Multi-objective optimization of hybrid electrical vehicle based on immune genetic algorithm

doi:10.3778/j.issn.1002-8331.1609-0017

Abstract

Abstract: A muti-objective optimal model for minimizing fuel consumption, emission of CO and HC, and NOx emission is established, optimization variable for parameters of the powertrain and control strategy, dynamic performance and battery state of charge equilibrium as constraint conditions. By using the weight coefficient method, multi-objective optimization problems are transformed into a single objective optimization function. A multi-objective evolutionary algorithm based on immune genetic algorithm for the parameters is proposed. This algorithm uses a real coding method to represent antibody and functions of ADVISOR to establish a combine simulation model. Simulation results show that the fuel consumption is decreased, and emissions of CO and HC are reduced effectively, it also shows the proposed algorithm is able to perform the multi-objective optimization design of HEV and provide a set of alternative optimal parameters of better fuel economy and emission performance for designer.

Key words: powertrain, control strategy, immune genetic algorithm, parameters optimization

摘要： 以混合动力汽车传动系统参数与控制策略参数为优化变量，以最小燃油消耗和尾气排放量（CO+HC+NOx）为优化目标，以动力性能与电池荷电状态平衡作为约束条件，建立多目标优化模型，并使用权重系数法将多目标函数优化问题转化为单目标问题。提出了基于免疫遗传算法优化混合动力汽车参数的优化方法，该算法采用实数编码，通过调用ADVISOR的后台函数，建立联合优化仿真模型。仿真结果表明，该算法可有效降低车辆的燃油消耗，减少CO与HC排放量，能够较好地解决带有约束的混合动力汽车的多目标多参数优化问题，可以获得一组具有低油耗与低污染物排放的传动系统与控制策略参数，供决策者选择。

关键词: 传动系统, 控制策略, 免疫遗传算法, 参数优化

LI Jie1, LI Hao2, ZHAO Xinqu1. Multi-objective optimization of hybrid electrical vehicle based on immune genetic algorithm[J]. Computer Engineering and Applications, 2018, 54(4): 237-243.

李婕1，李昊2，赵新蕖1. 免疫遗传算法的混合动力汽车多目标优化[J]. 计算机工程与应用, 2018, 54(4): 237-243.

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Multi-objective optimization of hybrid electrical vehicle based on immune genetic algorithm

免疫遗传算法的混合动力汽车多目标优化

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