Research on Soft-Sensing Technique of Vehicle State Parameters

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For meeting the needs of vehicle control system to some real-time parameters, a kind of soft-sensing technique was studied by using the extended Kalman filter theory in this paper. The specific flow for the application of extended Kalman filtering theory about the estimation of vehicle state parameters was presented detailedly, a state observer was established based on the vehicle dynamic model of a 2 degree of freedom. Simulation results indicate that these types of soft-sensing technique can measure some key state information of vehicle easily and accurately, such as longitudinal and lateral acceleration, and get real-time state estimates required by vehicle control system. Hence, it has very important meaning in reducing the cost of control system of vehicle.

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1212-1215

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October 2013

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Aleksander Hac, Melinda D. Simpson. Estimation of vehicle side slip angle and yaw rate. SAE 2000 World Congress, SAE Technical Paper Series 2000-01-0696.

DOI: 10.4271/2000-01-0696

Google Scholar

[2] G Hodgson, M C Best. A parameter identifying a Kalman filter observer for vehicle handling dynamics. Automobile Engineering, Vol. 220, 1063-1072.

DOI: 10.1243/09544070d18304

Google Scholar

[3] Changguan YU. Modern control theory and its application. Harbin: Harbin Institute of Technology Press, (2005).

Google Scholar

[4] Furukawa Y, Yuhara N, Sano S et al. A review of four-wheel steering studies from the viewpoint of vehicle dynamics and control, Vehicle System Dynamics, 1989, 18: 151-186.

DOI: 10.1080/00423118908968917

Google Scholar

[5] Donghyun Kim, Hyunsoo Kim. Vehicle stability control with regenerative braking and electronic brake force distribution for a four-wheel drive hybrid electric vehicle. Automobile Engineering: vol. 220, 683-693.

DOI: 10.1243/09544070d00605

Google Scholar

[6] Lang WEI. An analysis of vehicle dynamic simulating tire model used in collisions accidents. Journal of Xi'an Highway University, 1999, 19(2): 73-76.

Google Scholar

[7] Junjie He, D A Crolla, M C Levesley, and W J Manning. Coordination of active steering, driveline, and braking for integrated vehicle dynamics control. Automobile Engineering, vol. 220, 1401-1421.

DOI: 10.1243/09544070jauto265

Google Scholar