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This study deals with the implementation of an efficient control strategy using battery-supercapacitor for an electric vehicle driven by a permanent-magnet synchronous motor. The whole system consists of two parts: the energy management system and the traction system. The energy management system is mainly composed of a fuzzy-Lyapunov controller used to regulate both the current sources and the DC-bus voltage. For the traction system, direct torque control based on 12 sectors drive is used for the control of the motor to ensure both decoupled flux and torque with low ripple compared with the conventional Direct Torque Control (DTC). To make a comparative study for the energy management system, two strategies of energy management have been implemented. The first strategy does not include the regulation of the supercapacitor voltage, whereas the second one is based on the regulation of the supercapacitor voltage to protect it from deep discharge and avoid short circuit. The experimental tests were implemented using two dSPACE 1104 implementation boards. The results show that the system under the second energy control strategy works perfectly and verifies the effectiveness of the proposed control technique.

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The Energy Management Strategy (EMS) in Fuel Cell Hybrid Electric Vehicles (FCHEVs) is the key part to enhance optimal power distribution. Indeed, the most recent works are focusing on optimizing hydrogen consumption, without taking into consideration the degradation of embedded energy sources. In order to overcome this lack of knowledge, this paper describes a new health-conscious EMS algorithm based on Model Predictive Control (MPC), which aims to minimize the battery degradation to extend its lifetime. In this proposed algorithm, the health-conscious EMS is normalized in order to address its multi-objective optimization. Then, weighting factors are assigned in the objective function to minimize the selected criteria. Compared to most EMSs based on optimization techniques, this proposed approach does not require any information about the speed profile, which allows it to be used for real-time control of FCHEV. The achieved simulation results show that the proposed approach reduces the economic cost up to 50% for some speed profile, keeping the battery pack in a safe range and significantly reducing energy sources degradation. The proposed health-conscious EMS has been validated experimentally and its online operation ability clearly highlighted on a PEMFC delivery postal vehicle.

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