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State Estimation of Distributed Electric Vehicles

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State Estimation and Coordinated Control for Distributed Electric Vehicles

Part of the book series: Springer Theses ((Springer Theses))

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Abstract

State parameter estimation is the foundation for dynamic control of vehicles. Rational utilization of structural features of distributed electric vehicles and observation of multiple state parameters by integration of multiple state parameters of vehicles are essential and basic work to realize dynamic control targets of distributed electric vehicles. Precision of state estimation directly determines dynamic control performance and the state parameter obtained from observation can not only be applied to coordinated control mentioned but also to other follow-up control processes. Current state estimation method of vehicles mainly originates from traditional vehicles, lacking consideration for inherent features of distributed electric vehicles. Aiming at the existing defects, this chapter made full use of the advantages in state estimation of distributed electric vehicles, and proposed the scheme of synthesizing multi-information and integrating multiple methods for combined observation of multiple states. Observation of state parameter lays foundation for dynamic control over distributed electric vehicles. Overall structure of state estimation system of distributed electric vehicles has been designed in Chap. 2, and this chapter will study state estimation methods of vehicles, including vehicle motion state observation (including longitudinal vehicle velocity, side slip angle and yaw rate), vehicle acting force observation (including lateral force and vertical force of tire), mass observation of full vehicle and gradient observation of road surface. According to state observation structure mentioned in Chap. 2 of this dissertation, estimation of mass of full vehicle, road surface gradient and vertical force of tire shall be completed first, on the basis of which non-linear vehicle dynamic model is built. Meanwhile, considering the strong non-linearity of the built vehicle dynamic model, unscented particle filter is designed to make combined observation of state of multiple wheels.

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Authors and Affiliations

  1. Department of Automotive Engineering, Tsinghua University, Beijing, China

    Wenbo Chu

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  1. Wenbo Chu
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Correspondence to Wenbo Chu .

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Chu, W. (2016). State Estimation of Distributed Electric Vehicles. In: State Estimation and Coordinated Control for Distributed Electric Vehicles. Springer Theses. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48708-2_3

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  • DOI: https://doi.org/10.1007/978-3-662-48708-2_3

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-48706-8

  • Online ISBN: 978-3-662-48708-2

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