Mehdi Sellali | Université de Technologie de Belfort-Montbéliard (UTBM) (original) (raw)

Papers by Mehdi Sellali

Research paper thumbnail of Multi-Objective Optimization-Based Health-Conscious Predictive Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles

Energies

The Energy Management Strategy (EMS) in Fuel Cell Hybrid Electric Vehicles (FCHEVs) is the key pa... more 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...

Research paper thumbnail of A Novel Energy Management Strategy in Electric Vehicle Based on H∞ Self-Gain Scheduled for Linear Parameter Varying Systems

IEEE Transactions on Energy Conversion, 2020

The present paper exhibits a real time assessment of a robust Energy Management Strategy (EMS) fo... more The present paper exhibits a real time assessment of a robust Energy Management Strategy (EMS) for battery-super capacitor (SC) Hybrid Energy Storage System (HESS). The proposed algorithm, dedicated to an electric vehicular application, is based on a self-gain scheduled controller, which guarantees the H∞ performance for a class of linear parameter varying (LPV) systems. Assuming that the duty cycle of the involved DC-DC converters are considered as the variable parameters, that can be captured in real time, and forwarded to the controller to ensure both; the performance and robustness of the closed-loop system. The subsequent controller is therefore time-varying and it is automatically scheduled according to each parameter variation. This algorithm has been validated through experimental results provided by a tailor-made test bench including both the HESS and the vehicle traction emulation system. The experimental results demonstrate the overall stability of the system, where the proposed LPV supervisor successfully accomplishes a power frequency splitting in an adequate way, respecting the dynamic of the sources. The proposed solution provides significant performances for different speed levels.

Research paper thumbnail of Hardware implementation of an improved control strategy for battery/super capacitor hybrid system in electric vehicles

IET Electrical Systems in Transportation, 2019

This study deals with the implementation of an efficient control strategy using battery-supercapa... more 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.

Research paper thumbnail of Fault‐tolerant control of a smart PV‐grid hybrid system

IET Renewable Power Generation, 2019

This study deals with a fault-tolerant control of a smart PV-grid plant. The small scale system i... more This study deals with a fault-tolerant control of a smart PV-grid plant. The small scale system is dedicated to a stationary alternative current load and it consists of a photovoltaic module, supported by a single-phase grid. To ensure a smart permutation between the two proposed operation modes, a fuzzy logic-based power management algorithm is designed and implemented. In case of a subsystem failure, a fault-tolerant control technique is adopted to maintain the service continuity. In this study, two scenarios are proposed. The first concerns a load current sensor failure, where a material redundancy is adopted through the use of two observers, selected via a voting algorithm. The second deals to sense the system ability to maintain the service continuity in the worst case, where a grid blackout (grid-off) is planned. In this scenario, an additional functioning mode is added to reconfigure the control strategy. To prove the effectiveness of the proposed algorithms, the obtained experimental results with a given load profile are presented and commented.

Research paper thumbnail of Multi-Objective Optimization-Based Health-Conscious Predictive Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles

Energies

The Energy Management Strategy (EMS) in Fuel Cell Hybrid Electric Vehicles (FCHEVs) is the key pa... more 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...

Research paper thumbnail of A Novel Energy Management Strategy in Electric Vehicle Based on H∞ Self-Gain Scheduled for Linear Parameter Varying Systems

IEEE Transactions on Energy Conversion, 2020

The present paper exhibits a real time assessment of a robust Energy Management Strategy (EMS) fo... more The present paper exhibits a real time assessment of a robust Energy Management Strategy (EMS) for battery-super capacitor (SC) Hybrid Energy Storage System (HESS). The proposed algorithm, dedicated to an electric vehicular application, is based on a self-gain scheduled controller, which guarantees the H∞ performance for a class of linear parameter varying (LPV) systems. Assuming that the duty cycle of the involved DC-DC converters are considered as the variable parameters, that can be captured in real time, and forwarded to the controller to ensure both; the performance and robustness of the closed-loop system. The subsequent controller is therefore time-varying and it is automatically scheduled according to each parameter variation. This algorithm has been validated through experimental results provided by a tailor-made test bench including both the HESS and the vehicle traction emulation system. The experimental results demonstrate the overall stability of the system, where the proposed LPV supervisor successfully accomplishes a power frequency splitting in an adequate way, respecting the dynamic of the sources. The proposed solution provides significant performances for different speed levels.

Research paper thumbnail of Hardware implementation of an improved control strategy for battery/super capacitor hybrid system in electric vehicles

IET Electrical Systems in Transportation, 2019

This study deals with the implementation of an efficient control strategy using battery-supercapa... more 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.

Research paper thumbnail of Fault‐tolerant control of a smart PV‐grid hybrid system

IET Renewable Power Generation, 2019

This study deals with a fault-tolerant control of a smart PV-grid plant. The small scale system i... more This study deals with a fault-tolerant control of a smart PV-grid plant. The small scale system is dedicated to a stationary alternative current load and it consists of a photovoltaic module, supported by a single-phase grid. To ensure a smart permutation between the two proposed operation modes, a fuzzy logic-based power management algorithm is designed and implemented. In case of a subsystem failure, a fault-tolerant control technique is adopted to maintain the service continuity. In this study, two scenarios are proposed. The first concerns a load current sensor failure, where a material redundancy is adopted through the use of two observers, selected via a voting algorithm. The second deals to sense the system ability to maintain the service continuity in the worst case, where a grid blackout (grid-off) is planned. In this scenario, an additional functioning mode is added to reconfigure the control strategy. To prove the effectiveness of the proposed algorithms, the obtained experimental results with a given load profile are presented and commented.