Online energy management strategy of a hybrid fuel cell/battery/ultracapacitor vehicular power system

Azib, Toufik; Larouci, Cherif; Chaibet, Ahmed; Boukhnifer, Moussa

doi:10.1002/tee.22004

Cited by 34 publications

(18 citation statements)

References 28 publications

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“…The stability condition is verified for any positive value of K bat . The control signal that ensures the convergence of the battery current to its setpoint is given in Equation (16).…”

Section: Battery Current Controlmentioning

confidence: 99%

“…A hybrid Electric Storage System (ESS) consisting of a Battery (BAT) and a pack of Ultracapacitors (UC) is used in this paper. It offers the advantages to assist the fuel cell and to recover regenerative energy at braking [15][16][17]. This hybrid ESS could be replaced by the new technology of lithium-ion capacitors in the next few years [18,19].…”

Section: Introductionmentioning

confidence: 99%

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Auto-Adaptive Filtering-Based Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles

et al. 2018

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The global need to solve pollution problems has conducted automotive engineers to promote the development and the use of electric vehicle technologies. This paper focuses on the fuel cell hybrid electric vehicle which uses a proton exchange membrane fuel cell as a main source associated to hybrid storage device: lithium ion battery and ultracapacitors. A common interest in such technology is to spread out the energy flow between its different sources in order to satisfy the power demand for any requested mission. However, the challenging task stills the optimization of this split to reduce hydrogen consumption and respect, at the same time, the system limitations such as admissible limits of storage system capacities and battery current variation. An adaptive filtering-based energy management strategy is proposed in this paper to ensure an optimum distribution of the energy between the sources taking into account dynamic and energetic constraints of each device. For more performance, a fuzzy logic system is used to adapt the frequency of separation with the system state evolution. A sliding mode control is applied to control electric characteristics (voltage and currents) in the considered hybrid power supply. Simulation results, obtained under MATLAB R /SimPowerSystems R for four driving cycles are presented. The proposed strategy achieved good performances by respecting the ultracapacitors state of charge while preserving the battery lifetime under various driving missions.

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“…The stability condition is verified for any positive value of K bat . The control signal that ensures the convergence of the battery current to its setpoint is given in Equation (16).…”

Section: Battery Current Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Auto-Adaptive Filtering-Based Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles

et al. 2018

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“…The performance of the full order LP V /H ∞ controller is compared with that of the reduced-order one. To this end, the considered criterion is the cost function in (9) and both H ∞ , and H 2 norms of the closed-loop system. The comparison is done using the maximum obtained values among all vertices of the polytope and shown in Table 1.…”

Section: Controller Order Reductionmentioning

confidence: 99%

“…In order to achieve hybridization between the three power sources (fuel cell is main power source, battery and supercapacitor are auxiliary power sources), many configuration topologies are proposed regarding the number of components, energy management complexity and performance reliability. There are three main topological architectures: series, parallel, and cascaded [9,10,11]. In this paper, the parallel structure is chosen due to its flexibility to adapt the system parameters such that DC-bus value, sources' independence, and even the facility to replace or to add more power sources (photovoltaic panels, grid electricity, etc...).…”

Section: Introductionmentioning

confidence: 99%

Power sources coordination through multivariable linear parameter‐varying/ control with application to multi‐source electric vehicles

Nwesaty

Bratcu

Sename

2016

IET Control Theory & Applications

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In this paper the problem of multi-source power sharing strategy within electric vehicles is considered. Three different kinds of power sources-fuel cell, battery and supercapacitor-compose the power supply system, where all sources are current-controlled and paralleled together with their associated DC-DC converters on a common DC-link. The DC-link voltage must be regulated regardless of load variations corresponding to the driving cycle. The proposed strategy is a robust control solution using a MIMO LPV/H∞ controller which provides the three current references with respect to source frequency characteristics. The selection of the weighting functions is guided by a genetic algorithm whose optimization criterion expresses the frequency separation requirements. A reduced-order version of the LPV/H∞ controller is also proposed to handle an embedded implementation with limited computational burden. The nonlinear multi-source system is simulated in MATLAB R /Simulink R using two different types of driving cycles: the driving cycle of IFSTTAR (Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux) and a constant load profile used in order to illustrate system steady-state behaviour. Simulation results show good performance in supplying the load at constant DC-link voltage according to user-configured frequency-separation power sharing strategy. When assessed against the classical-PI-based filtering strategy taken as base-line, the proposed strategy offers the possibility of integrating a variety of constraints into a systematic design procedure, whose result guarantees stability and performance robustness.

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“…In the electromobility three main hybridization topologies are available depending on the number of components, energy management complexity and performance reliability: series, parallel, and cascaded [4]- [6]. In this paper, a parallel structure of three sources in a DC system -fuel cell, battery and supercapacitor -is chosen due to its flexibility (sources' independent operation, facility to replace/add power sources, etc.).…”

Section: Introductionmentioning

confidence: 99%

Robust Energy Management System for Multi-Source DC Energy Systems—Real-Time Setup and Validation

Nwesaty

Bratcu

Ravey

et al. 2020

IEEE Trans. Contr. Syst. Technol.

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This paper aims at providing a proof of concept of a systematically designed LPV/H∞-based energy management system (EMS) for coordinated multi-variable control of multi-source electrical systems. A three-source electrical system representing the power supply system on board of an electric vehicle has been chosen as a representative example of irregular and generally not a priori known load variation. The power supply system is composed of fuel cell, battery and supercapacitor. Each power source is coupled to a DC-DC converter, all converters being connected in parallel to a common DC-bus in order to feed the load represented by the vehicle's electrical motor. The system is modelled as an LPV system -as its operating point depends on the load -and the control objectives are cast into the H∞ formalism as a disturbance-rejection problem.A dedicated hardware-in-the-loop system was built for proof of concept purpose, with real-world battery and supercapacitor being used, while the fuel cell system is entirely emulated. A dSPACE MicroAutoBox ® II device embeds the designed EMS, due to its flexibility and ease of programming with MATLAB ® . A driving cycle from IFSTTAR (Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux) is chosen as a pertinent scenario of load variation due to its rich frequency content able to challenge all the three sources. Effectiveness of the EMS is assessed in relation to the imposed control objectives -DC-bus voltage regulation, dynamical separation of power sources' current variations depending on the specialization range of each source, and imposing desired steady-state behavior for each of the three power sources -with very promising results.

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Online energy management strategy of a hybrid fuel cell/battery/ultracapacitor vehicular power system

Cited by 34 publications

References 28 publications

Auto-Adaptive Filtering-Based Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles

Auto-Adaptive Filtering-Based Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles

Power sources coordination through multivariable linear parameter‐varying/ control with application to multi‐source electric vehicles

Robust Energy Management System for Multi-Source DC Energy Systems—Real-Time Setup and Validation

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