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Journal of System Simulation

Abstract

Abstract: To solve the problems of environmental interference, sensor noise and poor tracking stability of time-varying speed, an improved MPC (model predictive control) algorithm based on KF (kalman filtering) is proposed. The longitudinal kinematics model of CACC(cooperative adaptive cruise control)between vehicles is established and the discrete state space equation is created. KF is used to reduce the noise of state variables, and at the same time, the prediction model is designed for robustness. The CACC control objectives are analyzed under different working conditions and the objective optimization functions are created. Verify by building Simulink and CarSim co-simulation model, the simulation results indicate that the improved MPC algorithm performs better, which improves economy of the fuel and driving comfort of vehicles, achieves stable tracking of time-varying speed.

First Page

2087

Revised Date

2021-07-02

Last Page

2097

CLC

U471.15;TP391

Recommended Citation

Qiming Wang, Jiangyue Jiang, Zhichao Lü, Hanzu Zhang. Research on Cooperative Adaptive Cruise Control Strategy Based on Improved MPC[J]. Journal of System Simulation, 2022, 34(09): 2087-2097.

DOI

10.16182/j.issn1004731x.joss.21-0388

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