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Electric machine differential for vehicle traction control and stability control.

机译:用于车辆牵引力控制和稳定性控制的电机差速器。

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摘要

Evolving requirements in energy efficiency and tightening regulations for reliable electric drivetrains drive the advancement of the hybrid electric (HEV) and full electric vehicle (EV) technology. Different configurations of EV and HEV architectures are evaluated for their performance. The future technology is trending towards utilizing distinctive properties in electric machines to not only to improve efficiency but also to realize advanced road adhesion controls and vehicle stability controls. Electric machine differential (EMD) is such a concept under current investigation for applications in the near future. Reliability of a power train is critical. Therefore, sophisticated fault detection schemes are essential in guaranteeing reliable operation of a complex system such as an EMD. The research presented here emphasize on implementation of a 4kW electric machine differential, a novel single open phase fault diagnostic scheme, an implementation of a real time slip optimization algorithm and an electric machine differential based yaw stability improvement study. The proposed d-q current signature based SPO fault diagnostic algorithm detects the fault within one electrical cycle. The EMD based extremum seeking slip optimization algorithm reduces stopping distance by 30% compared to hydraulic braking based ABS.
机译:不断提高的能效要求和对可靠的电动传动系统的严格规定,推动了混合电动(HEV)和全电动汽车(EV)技术的发展。评估EV和HEV架构的不同配置的性能。未来的技术正在趋向于利用电机的独特性能,以不仅提高效率,而且实现先进的道路附着力控制和车辆稳定性控制。电机差速器(EMD)是目前正在研究中的一种概念,用于不久的将来。动力总成的可靠性至关重要。因此,复杂的故障检测方案对于保证诸如EMD的复杂系统的可靠运行至关重要。这里提出的研究重点在于4kW电机差速器的实现,新颖的单相断相故障诊断方案,实时滑差优化算法的实现以及基于电机差速器的偏航稳定性改进研究。提出的基于d-q电流签名的SPO故障诊断算法可在一个电周期内检测到故障。与基于液压制动的ABS相比,基于EMD的极值搜寻滑移优化算法将制动距离减少了30%。

著录项

  • 作者

    Kuruppu, Sandun Shivantha.;

  • 作者单位

    Purdue University.;

  • 授予单位 Purdue University.;
  • 学科 Engineering Electronics and Electrical.;Energy.;Engineering Mechanical.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 167 p.
  • 总页数 167
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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