On the Use of Genetic Algorithm to Optimize the On-board Energy Management of a Hybrid Solar Vehicle

I. Arsie, R. D. Martino, G. Rizzo, M. Sorrentino
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引用次数: 29

Abstract

This paper deals with the development of a prototype of Hybrid Solar Vehicle (HSV) with series structure. This activity has been also conducted in the framework of the European Union funded Leonardo project “Energy Conversion Systems and Their Environmental Impact”, a project with research and educational objectives. A study on supervisory control for hybrid solar vehicles and some preliminary tests performed on the road are presented. Previous results obtained by a model for HSV optimal design have confirmed the relevant benefits of such vehicles with respect to conventional cars in case of intermittent use in urban driving (city-car), and that economical feasibility could be achieved in a near future. Due to the series-powertrain adopted for the HSV prototype, an intermittent use of the ICE (Internal Combustion Engine) powering the electric generator is possible, thus avoiding part-load low-efficient engine operations. The best ICE power trajectory is determined via genetic algorithm optimization accounting for fuel mileage as well as battery state of charge, also considering solar contribution during parking mode. The experimental set up used for data logging, real-time monitoring and control of the prototype is also presented, and the results obtained with different road tests discussed.
利用遗传算法优化混合动力太阳能汽车的车载能量管理
本文研究了一种串联结构的混合动力太阳能汽车(HSV)样机的研制。这项活动也在欧洲联盟资助的列奥纳多项目“能源转换系统及其环境影响”框架内进行,该项目具有研究和教育目标。对混合动力太阳能汽车的监控系统进行了研究,并进行了初步的道路试验。先前通过HSV优化设计模型获得的结果已经证实,在城市驾驶中间歇性使用时,HSV车辆相对于传统汽车的相关效益(城市车),并且在不久的将来可以实现经济可行性。由于HSV原型采用了串联动力系统,因此可以间歇性地使用内燃机(内燃机)为发电机供电,从而避免了部分负荷低效率的发动机运行。考虑到燃油里程和电池充电状态,同时考虑到停车模式下太阳能的贡献,通过遗传算法优化确定最佳ICE功率轨迹。介绍了用于样机数据记录、实时监测和控制的实验装置,并讨论了不同道路试验的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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