融合整车质量估计的电动汽车坡道识别

doi:10.13229/j.cnki.jdxbgxb.20230625

Abstract

Abstract:

Aiming at the problems that the existing ramp recognition algorithms have poor adaptability to the conditions and are unable to satisfy the application requirements of mass production vehicles， an electric vehicle slope recognition method based on vehicle mass estimation was proposed. Firstly， the vehicle longitudinal dynamics model was established， and the signal characteristics of the acceleration sensor under the actual vehicle conditions were analyzed. The least square vehicle mass estimation strategy with forgetting factor was constructed to obtain the vehicle mass directly under the starting condition. Ramp recognition algorithms were designed for static parking and dynamic driving scenarios. In the static scenario， the filter latch strategy was used to deal with the interference factors such as activities in the vehicle. In the dynamic scenario， the Kalman filter algorithm based on measurement noise adaptation was designed to realize the fusion estimation of dynamic observation and kinematic observation for the slope. The effectiveness of the method was verified by Simulink-CarSim joint simulation. Finally， the real vehicle test was completed on Chery new energy's mass production electric vehicle platform and domain controller. The road test results show that the mass estimation error is less than ±10 kg； the static estimation error of the slope is less than 0.001 rad， and the dynamic error is within 0.005 rad. The estimation accuracy and stability are greatly improved， which ensures the environmental adaptability of the intelligent electric vehicles.

Key words: electric vehicle, slope recognition, mass estimation, adaptive filter

CLC Number:

U461.72

Lin LIU,Yan-jun REN,Tong SHEN,Guo-dong YIN,You-jing ZHANG. Electric vehicle ramp recognition based on fusion of vehicle mass estimation[J].Journal of Jilin University(Engineering and Technology Edition), 2025, 55(3): 846-856.

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物理量	符号	数值
整备质量/kg	M	1 673
风阻系数	C_d	0.71
空气密度/［N·（s²·m^-4）］	ρ	1.2
车轮滚动半径/m	R_w	0.316
滚动阻力系数	f₀	0.008
旋转质量系数	δ	1.03

Electric vehicle ramp recognition based on fusion of vehicle mass estimation

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