سال انتشار:

2020

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عنوان انگلیسی مقاله:

Energy optimization of electric vehicle’s acceleration process based on reinforcement learning

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ترجمه فارسی عنوان مقاله:

بهینه سازی انرژی در روند شتاب خودروی الکتریکی بر اساس یادگیری تقویتی

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منبع:

Sciencedirect - Elsevier - Journal of Cleaner Production, 248 (2020) 119302. doi:10.1016/j.jclepro.2019.119302

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نویسنده:

Hongwen He a, *, Jianfei Cao a, Xing Cui b

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چکیده انگلیسی:

Under the situation of unmanned driving, the energy consumption in an electric vehicle’s acceleration process can be reduced by controlling the driving behavior. So in this paper, a pedal control strategy which could optimize the energy consumption of electric vehicle’s acceleration process is proposed. The strategy is generated by the training results of reinforcement learning framework and the specific method of building such framework is discussed in details. Based on the training results of Q-learningbased algorithm, the relationship between the proportion of energy consumption reduction and vehicle’s acceleration time is analyzed, which illustrates the energy-saving potential of the algorithm. In order to improve the control effect of the strategy, an updated algorithm framework based on Deep Q-learning (DQN) is proposed and an improved pedal’s control strategy is obtained. Compared with the strategy obtained by Q-learning-based algorithm, the improved strategy not only achieves the same energysaving effect, but also guarantees the stability of control effect, which is more suitable for actual use.
Keywords: Unmanned driving | Electric vehicles | Pedal control stratgey | Energy optimization | Q-learning | Deep Q-learning

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قیمت: رایگان

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توضیحات اضافی:

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