论文标题
考虑再生制动的电动汽车生态驾驶的基于GA的方法
A GA-based Approach to Eco-driving of Electric Vehicles Considering Regenerative Braking
论文作者
论文摘要
随着低碳运输技术（特别是电动汽车）的部署正在增加，其生态驾驶的概念正在引起极大的关注。与没有再生制动能力的常规内燃机车辆中使用的生态驱动技术相反，本文提出了一种基于遗传算法（GA）的生态驱动技术，用于考虑再生制动的电动汽车。在建议的方法中，使用GA搜索了EV驱动周期中变量的最佳或近乎最佳组合。所提出的方法首先产生染色体的初始群体，其中所有正在考虑的变量均在每个染色体中编码。这种染色体的种群通过一代世代相传的跨界，突变和基于精英的选择，这导致驱动周期的能量消耗最少。使用两个案例研究对所提出的方法进行了验证。案例研究的结果表明，该方法在计算最小能量驱动周期中的能力。
As the deployment of low carbon transportation technologies, specifically electric vehicles (EVs), is increasing, the concept of their eco-driving is gaining significant attention. Contrary to the eco-driving techniques used in conventional internal combustion engine vehicles that do not have the capability of regenerative braking, this paper proposes a genetic algorithm (GA)-based eco-driving technique for EVs considering regenerative braking. In the proposed approach, the optimal or near-optimal combination of variables in the driving cycle of EVs is searched using GA. The proposed approach starts by generating an initial population of chromosomes, where all variables under consideration are encoded in each chromosome. This population of chromosomes is passed through crossover, mutation, and elitist-based selection over a certain number of generations, which results in a driving cycle with the least energy consumption. The proposed method is verified using two case studies. The results of the case studies show the capability of the proposed method in computing the minimum energy driving cycle.
