Affiliation:
1. School of Electronic Engineering, Heilongjiang University, Harbin 150080, China
2. Key Laboratory of Information Fusion Estimation and Detection, Harbin 150080, China
Abstract
Energy-optimal adaptive cruise control (EACC) is becoming increasingly popular due to its ability to save energy. Considering the negative impacts of system noise on the EACC, an improved modified model predictive control (MPC) is proposed, which combines the Sage-Husaadaptive Kalman filter (SHAKF), the cubature Kalman filter (CKF), and the back-propagation neural network (BPNN). The proposed MPC improves safety and tracking performance while further reducing energy consumption. The final simulation results show that the proposed algorithm has a stronger energy-saving capability compared to previous studies and always maintains an appropriate relative distance and relative speed to the vehicle in front, verifying the effectiveness of the proposed algorithm.
Funder
National Natural Science Foundation (NNSF) of China
University Basic Research foundation of Heilongjiang Province
Outstanding Youth Foundation of Heilongjiang University
Key Laboratory of Information Fusion Estimation and Detection, Heilongjiang Province
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Cited by
5 articles.
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