Optimized Powermanagement for Human Driver-HEV Using Online Identification of Velocity Patterns

机译：使用速度模式的在线识别为人类驾驶员-HEV优化动力管理

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Inspite of the advances in hybrid electric vehicles (HEVs), most powermanagement and optimization techniques are developed for predeﬁned driving cycles. In this contribution, an optimal solution for the future is provided, which encompasses multiple aspects of HEV control. A new embedded- online optimization approach is considered. Instead of carrying out online powermangement optimization with computationally extensive algorithms, the entire task is divided into two parts: an ofﬂine part where optimal parameters for different velocity values of a human driver are recorded, an online part where these parameters along with identiﬁcation and prediction algorithms are used to display the optimal information to the driver online. The online display of results where a real human inﬂuences the HEV by driving via a real-time interface show the applicability of this approach.

机译：尽管混合动力汽车（HEV）取得了进步，但大多数动力管理和优化技术仍针对预定的驾驶周期而开发。在此贡献中，提供了针对未来的最佳解决方案，其中包括混合动力汽车控制的多个方面。考虑了一种新的嵌入式在线优化方法。代替使用计算量大的算法进行在线动力管理优化，整个任务分为两个部分：一个是常规部分，其中记录了驾驶员不同速度值的最佳参数;另一个是在线部分，其中这些参数以及识别和预测算法用于向驾驶员在线显示最佳信息。在线显示结果，在此情况下，真实的人通过实时界面驾驶会对HEV产生影响，从而表明该方法的适用性。

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《IEEE Vehicle Power and Propulsion Conference》|2015年|1-5|共5页
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Moulik Bedatri; Wang Jiao; Soffker Dirk;
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Hybrid electric vehicles; Mechanical power transmission; Optimization; Predictive models; Table lookup; Torque;

机译：混合动力汽车;机械动力传递;优化;预测模型;表查询;扭力;

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Optimized Powermanagement for Human Driver-HEV Using Online Identification of Velocity Patterns

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