Optimal energy management of hybrid electric vehicles requires a priori information regarding future driving conditions; the acquisition and processing of this information is nevertheless often neglected in academic research. This paper introduces a commuter route optimized energy management system, where the bulk of the computations are performed on a server. The idea is to identify commuter routes from historical driving data, using hierarchical agglomerative clustering, and then precompute an optimal solution to the energy management control problem with dynamic programming; the obtained solution can then be transmitted to the vehicle in the form of a lookup table. To investigate the potential of such a system, a simulation study is performed using a detailed vehicle model implemented in the Autonomie simulation environment for MATLAB/Simulink. The simulation results for a plug-in hybrid electric vehicle indicate that the average fuel consumption along the commuter route(s) can be reduced by 4%–9% and battery usage by 10%–15%.
Commuter Route Optimized Energy Management of Hybrid Electric Vehicles
IEEE Transactions on Intelligent Transportation Systems ; 15 , 3 ; 1145-1154
2014-06-01
1802975 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Commuter Route Optimized Energy Management of Hybrid Electric Vehicles
Online Contents | 2014
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