Weighted multiple model control system for the stable steering performance of distributed drive electric vehicle

  • Ke ShiEmail author
  • Xiaofang Yuan
  • Guoming Huang
  • Zhixian Liu
Technical Paper


The steering performance of the distributed drive electric vehicle (DDEV) is an important research topic. Generally, DDEV works under various operating status with high switching frequency, while the conventional stability controller is only suitable for one special operating status. In addition, the lateral force saturation or deficiency always leads to the unstable steering performance. To achieve the stable steering performance under various operating status for DDEV, a novel weighted multiple model control system (WMMCS) is proposed in this paper. The proposed WMMCS consists of three parts, including a submodel set (SMS), a subcontroller set (SCS) and a weighted fusion unit (WFU). The SMS classifies the vehicle operating status into four typical operating modes and analyses their operating characteristics. The SCS designs the corresponding model predictive controller for each typical operating mode to realize the optimal four-wheel steering; then, the lateral force saturation or deficiency problem can be solved. The WFU analyses the matching degree between the actual state of DDEV and each submodel by the fuzzy logic; then, the control output of the WMMCS is calculated by the weighted signal of each subcontroller. The simulation is carried on the MATLAB, and the results show that the stable steering performance and smooth operating switching performance of DDEV can be achieved efficiently by the proposed WMMCS.


Distributed drive electric vehicle (DDEV) Stable steering performance Four-wheel steering (FWS) Weighted multiple model (WMM) Smooth switching Model predictive controller (MPC) 



This work was supported in part by National Key R\({ \& }\)D Program of China (No. 2017YFB1300900), National Natural Science Foundation of China (No. 61573133), Key Research and Development Program of Hunan Province of China (No. 2018GK2031).


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Copyright information

© The Brazilian Society of Mechanical Sciences and Engineering 2019

Authors and Affiliations

  • Ke Shi
    • 1
    • 2
    Email author
  • Xiaofang Yuan
    • 1
    • 2
  • Guoming Huang
    • 1
    • 2
  • Zhixian Liu
    • 1
    • 2
  1. 1.College of Electrical and Information EngineeringHunan UniversityChangshaChina
  2. 2.National Engineering Laboratory for Robot Vision Perception and ControlHunan UniversityChangshaChina

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