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

机译:利用遗传算法优化混合动力太阳能汽车的车载能量管理

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摘要

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.
机译:本文研究了具有串联结构的混合动力太阳能汽车(HSV)原型的开发。这项活动也是在欧盟资助的莱昂纳多项目“能源转换系统及其环境影响”的框架内进行的,该项目具有研究和教育目标。提出了混合动力太阳能汽车监督控制的研究以及在道路上进行的一些初步测试。通过HSV最佳设计模型获得的先前结果已经证实,在城市驾驶(城市汽车)间歇性使用的情况下,此类车辆相对于常规车辆具有相关优势,并且可以在不久的将来实现经济可行性。由于HSV原型采用了串联动力总成,因此可以间歇性地使用ICE(内燃机)为发电机供电,从而避免了部分负荷低效率发动机的运行。最佳ICE功率轨迹是通过遗传算法优化来确定的,该优化考虑了燃油里程以及电池充电状态,还考虑了停车模式下的太阳能贡献。还介绍了用于数据记录,实时监视和控制原型的实验装置,并讨论了通过不同路试获得的结果。

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