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Design, Control, and Validation of a Charge-Sustaining Parallel Hybrid Bicycle

机译:维持电荷的并联混合动力自行车的设计,控制和验证

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Traffic congestion, energy, and environmental considerations are boosting the interest for light electric vehicles. Electrically power-assisted cycles (EPACs) have great potential: they are cost effective, safe, easy to use, and have a small footprint. The two biggest disadvantages affecting EPACs are the need to recharge them and the added weight to the bicycle. To address these issues, a novel hybrid electric bike is presented. This contribution represents the first complete instance of a real-time electric bicycle–human body synergic control. The idea is to recover energy from the cyclist when she is most efficient and return it during low-efficiency pedaling. A control-oriented analysis of the cyclist’s metabolic efficiency is carried out to guide the design of the control algorithm. Three features are employed for this purpose: an -defined equivalent cycling efficiency based on oxygen consumption, a dynamic model for the state of fatigue (SoF), and heart rate (HR) measurements. The analysis of the equivalent cycling efficiency and SoF dynamics guide the design of a charge-sustaining assistance algorithm. The algorithm is designed and tuned through simulations. The proposed system is tested on subjects, and it is shown that it is capable of maintaining the battery charge; further tests indicate that improvements up to 25% in equivalent cycling efficiency and reduction in peak HR and SoF can be achieved for urban cycling.
机译:交通拥堵,能源和环境方面的考虑使对轻型电动汽车的兴趣增加。电动辅助循环(EPAC)具有巨大的潜力:它们具有成本效益,安全,易于使用且占地面积小的优点。影响EPAC的两个最大缺点是需要给它们充电以及增加自行车的重量。为了解决这些问题,提出了一种新颖的混合动力电动自行车。这一贡献代表了实时电动自行车与人体协同控制的第一个完整实例。这个想法是在骑自行车的人效率最高时回收能量,并在低效率的踩踏过程中将其返回。对骑车人的代谢效率进行了面向控制的分析,以指导控制算法的设计。为此,采用了三个功能:基于氧气消耗的定义的等效循环效率,疲劳状态(SoF)的动态模型和心率(HR)测量。对等效循环效率和SoF动力学的分析指导了电荷保持辅助算法的设计。该算法是通过仿真设计和调整的。所建议的系统已在受试者身上进行了测试,结果表明该系统能够保持电池电量。进一步的测试表明,对于城市自行车,等效自行车效率可提高25%,峰值HR和SoF降低。

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