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Energies 2018, 11(11), 3042; https://doi.org/10.3390/en11113042

Method for Switching between Traction and Brake Control for Speed Profile Optimization in Mountainous Situations

1
State Key Laboratory of Automotive Simulation and Control, Jilin University, Jilin 130022, China
2
Transportation College, Jilin University, Jilin 130022, China
*
Author to whom correspondence should be addressed.
Received: 16 October 2018 / Revised: 1 November 2018 / Accepted: 4 November 2018 / Published: 6 November 2018
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Abstract

Making full use of front road grade information to achieve the best fuel efficiency is important for intelligent vehicles. Normal theoretical studies pay too much attention to engine continuous feedback control. The theoretical foundation of switching between traction and brake control has been ignored. In mountainous terrain, both the engine and road slopes are energy sources. Switching between traction and brake control is the key point. This research focuses on broadening the normal control range. The comprehensive objective function that contains traction and brake control is built, and then the analytical switching control law is derived based on Pontryagin’s maximum principle (PMP). Analytical switching control laws express the mechanism of switching between traction and brake control for economic cruise control (ECC). Simulation results show that the model can solve the switch time and the entire speed profile precisely. Brake control is very important in downhill situations. The parameters in the objective function influence not only the switch time but also the switch process. This research offers a theoretical foundation for ECC with road slopes and can make onboard control more precise and efficient. View Full-Text
Keywords: economic cruise control; road slope; switch control; optimal control; heavy duty vehicle economic cruise control; road slope; switch control; optimal control; heavy duty vehicle
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Lin, N.; Zong, C.; Shi, S. Method for Switching between Traction and Brake Control for Speed Profile Optimization in Mountainous Situations. Energies 2018, 11, 3042.

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