Estimation of the vehicle speed in the driving mode for a hybrid electric car based on an unscented Kalman filter

Author:

Zhao Zhiguo1,Chen Haijun1,Yang Jie1,Wu Xiaowei1,Yu Zhuoping1

Affiliation:

1. Clean Energy Automotive Engineering Center, Tongji University, Shanghai, People’s Republic of China

Abstract

Preconditions for the effective implementation of a control strategy in an automobile’s active safety system rely on timely and accurate information on the vehicle’s running status, especially the vehicle speed. However, the vehicle speed cannot be measured directly without using advanced onboard sensors or specialized test equipment owing to their high mass production cost. In this study, a model-based method for estimating the vehicle speed in different driving modes is conducted in real time, which makes full use of information on the driving wheel’s torque for a four-wheel-drive hybrid car. First, a simulation platform that integrates the models of the powertrain system, the non-linear seven-degree-of-freedom vehicle dynamics system and the dynamic UniTire model is established. Next, an unscented Kalman filter algorithm is adopted to estimate the vehicle speed, and the estimated results and the simulated results are compared under different driving modes. Finally, real-vehicle tests at medium and low speeds are performed using a prototype car. The simulations and the test results confirm that the proposed unscented Kalman filter estimation algorithm without a linearizing truncation process can estimate the vehicle speed with high precision and strong adaptability.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Aerospace Engineering

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1. A Study on Lateral Stability Control of Distributed Drive Electric Vehicle Based on Fuzzy Adaptive Sliding Mode Control;International Journal of Automotive Technology;2024-05-18

2. State Estimation of Drive-by-Wire Chassis Vehicle Based on Dual Unscented Particle Filter Algorithm;Chinese Journal of Mechanical Engineering;2024-02-22

3. Longitudinal Speed Estimation of Multi-axle Distributed Drive Vehicle Based on Federal Kalman Filter;2023 7th CAA International Conference on Vehicular Control and Intelligence (CVCI);2023-10-27

4. On accurate estimation of vehicle lateral states based on an improved adaptive unscented Kalman filter;Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering;2022-10-31

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