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.
Recommended Citation
Wang, Qiming; Jiang, Jiangyue; Lü, Zhichao; and Zhang, Hanzu
(2022)
"Research on Cooperative Adaptive Cruise Control Strategy Based on Improved MPC,"
Journal of System Simulation: Vol. 34:
Iss.
9, Article 18.
DOI: 10.16182/j.issn1004731x.joss.21-0388
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol34/iss9/18
First Page
2087
Revised Date
2021-07-02
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.21-0388
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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