Analysis of the Adaptation of a New Method for Four-Wheel-Hub Electric Vehicle Online-Mass Estimation
Abstract
An accurate estimation of vehicle mass is important in automation of vehicle, vehicle following manoeuvres and traditional power train control schemes. It is easy for four-wheel-hub electric motor to get accurate speed signals and torque signals. Based on this feature we introduce a new algorithm for electric vehicle online-mass estimation by decoupling vehicle mass and road grade. In the Matlab/Simulink simulation environment we establish the new estimation algorithm model and an 18 degree of freedom vehicle model. We analyze the accuracy of this online-mass estimation method by changing the value of different parameters respectively, for example, different masses, different rolling resistances… This new mass estimation method is fast and reaches a high accuracy without extra sensors.
Keywords
Mass estimation Longitudinal dynamic Decoupling Algorithm SimulationNotes
Acknowledgments
This work was supported by National Basic Research Program of China. (No.2011CB711200)
References
- 1.ONISR, Les grandes donn’ees de laccidentologie (2005) In rapport ONISR. www.securiteroutiere.gouv.fr/infosref/observatoire/accidentologie/
- 2.Breen MT (1996) System and method for determining relative vehicle mass. No. 5,482,359Google Scholar
- 3.Genise T (1994) Control method system including determination of an updated value indicative of gross combination weight of vehicles. No. 5,490,063Google Scholar
- 4.Bae HS, Ryu J, Gerdes JC (2001) Road grade and vehicle parameter estimation for longitudinal control using GPS. In: Proceedings of the IEEE intelligent transportation systems conferenceGoogle Scholar
- 5.Vahidi A, Stefanopoulou A, Peng H (2005) Recursive least squares with forgetting for online estimation of vehicle mass and road grade: theory and experiments. Veh Syst Dyn 43:1, 31–55Google Scholar