Efficient ACC with Stop&Go Maneuvers for Hybrid Vehicle with Online Sub-Optimal Energy Management

Abstract : — This paper presents an Adaptive Cruise Control with Stop&Go (ACCwSG) maneuvers aiming to improve the fuel economy of a Hybrid Electric Vehicle (HEV). Within the scope of the given subject, an optimal offline optimization, based on Dynamic Programming (DP), is proposed in this work, permitting to have simultaneous speed profile optimization and optimal power split strategy of a series-parallel hybrid bus. Afterwards, the basis of the offline optimal strategy has been adapted in order to deal online with the current road profile and driver velocity demand. The proposed online and sub-optimal strategy uses mainly a Multi-Dimensional Database (MDD, which gives as output the speed profile and power-split set-points) and an appropriate interpolation technique in order to cope with the current bus situations. The MDD is obtained based on offline DP, while using specific protocol which cover a large possible space state of the vehicle situations and their corresponding optimal set-points. The developed strategy finds its practical application in ACCwSG for a heavy urban bus, which is subject to frequent highly energy consuming starts and stops phases. The present work is conducted on a dedicated high-fidelity dynamical model of the hybrid bus that was developed on MATLAB/TruckMaker software. Several simulations were performed to prove the efficiency of the proposed navigation strategy.
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Communication dans un congrès
11th International Workshop on Robot Motion and Control, Jul 2017, Wasowo, Poland. 2017 11th International Workshop on Robot Motion and Control (RoMoCo 2017)
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Dernière modification le : mercredi 31 octobre 2018 - 17:42:02
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  • HAL Id : hal-01659683, version 1

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Rustem Abdrakhmanov, Lounis Adouane. Efficient ACC with Stop&Go Maneuvers for Hybrid Vehicle with Online Sub-Optimal Energy Management. 11th International Workshop on Robot Motion and Control, Jul 2017, Wasowo, Poland. 2017 11th International Workshop on Robot Motion and Control (RoMoCo 2017). 〈hal-01659683〉

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