PEMFC Optimization Strategy with Auxiliary Power Source in Fuel Cell Hybrid Vehicle

one of the present-day implementation of fuel cell is acting as main power source in Fuel Cell Hybrid Vehicle (FCHV). This paper proposes some strategies to optimize the performance of Polymer Electrolyte Membrane Fuel Cell (PEMFC) implanted with auxiliary power source to construct a proper FCHV hybridization. The strategies consist of the most updated optimization method determined from three point of view i.e. Energy Storage System (ESS), hybridization topology and control system analysis. The goal of these strategies is to achieve an optimum hybridization with long lifetime, low cost, high efficiency, and hydrogen consumption rate improvement. The energy storage system strategy considers battery, supercapacitor, and high-speed flywheel as the most promising alternative auxiliary power source. The hybridization topology strategy analyzes the using of multiple storage devices injected with electronic components to bear a higher fuel economy and cost saving. The control system strategy employs nonlinear control system to optimize the ripple factor of the voltage and the current and using the AOC-EMS system to improve the hydrogen consumption rate. ECMS and BERS strategy based on Time-Triggered Controller Area Network (TTCAN) also promoted to optimize hydrogen consumption rate from recovered kinetic energy while in braking regeneration mode

Prioritizing Power demand response for Hydrogen PEMFC-Electric Vehicles using Hybrid Energy Storage

PEMFC powered Hybrid vehicle system is one of an interesting issue for the industry due to its high performances. The PEMFC cannot certainly ensure a sustained required energy in some scenarios. To solve this problem related to PEMFC transient response, a Hybrid Electrical Storage System (HES) is a potential candidate for a solution. The proposed Hybrid Storage system is comprised of the battery (BT) and a Super-Capacitor (SC) components. These components are included to control the hydrogen variations and the fast peak powers scenarios respectively. The SC is used to control PEMFC and the BT slow dynamics at the same times. An accurate Multi-Ways Energy Management System (MW-EMS) is proposed which aims to cooperate with the system components through SC/BT state of charge and a flux calculation. The simulation results are discussed and assessed using  MATLAB/ Simulink

Stratégies de gestion d’énergie pour véhicules électriques et hybride avec systèmes hybride de stockage d’énergie

Les véhicules électriques et hybrides font partie des éléments clés pour résoudre les problèmes de réchauffement de la planète et d'épuisement des ressources en combustibles fossiles dans le domaine du transporte. En raison des limites des différents systèmes de stockage et de conversion d’énergie en termes de puissance et d'énergie, les hybridations sont intéressantes pour les véhicules électriques (VE). Dans cette thèse, deux hybridations typiques sont étudiées • un sous-système de stockage d'énergie hybride combinant des batteries et des supercondensateurs (SC) ; • et un sous-système de traction hybride parallèle combinant moteur à combustion interne et entraînement électrique. Ces sources d'énergie et ces conversions combinées doivent être gérées dans le cadre de stratégies de gestion de l'énergie (SGE). Parmi celles-ci, les méthodes basées sur l'optimisation présentent un intérêt en raison de leur approche systématique et de leurs performances élevées. Néanmoins, ces méthodes sont souvent compliquées et demandent beaucoup de temps de calcul, ce qui peut être difficile à réaliser dans des applications réelles. L'objectif de cette thèse est de développer des SGE simples mais efficaces basées sur l'optimisation en temps réel pour un VE et un camion à traction hybride parallèle alimentés par des batteries et des SC (système de stockage hybride). Les complexités du système étudié sont réduites en utilisant la représentation macroscopique énergétique (REM). La REM permet de réaliser des modèles réduits pour la gestion de l'énergie au niveau de la supervision. La théorie du contrôle optimal est ensuite appliquée à ces modèles réduits pour réaliser des SGE en temps réel. Ces stratégies sont basées sur des réductions de modèle appropriées, mais elles sont systématiques et performantes. Les performances des SGE proposées sont vérifiées en simulation par comparaison avec l’optimum théorique (programmation dynamique). De plus, les capacités en temps réel des SGE développées sont validées via des expériences en « hardware-in-the-loop » à puissances réduites. Les résultats confirment les avantages des stratégies proposées développées par l'approche unifiée de la thèse.Abstract: Electric and hybrid vehicles are among the keys to solve the problems of global warming and exhausted fossil fuel resources in transportation sector. Due to the limits of energy sources and energy converters in terms of power and energy, hybridizations are of interest for future electrified vehicles. Two typical hybridizations are studied in this thesis: • hybrid energy storage subsystem combining batteries and supercapacitors (SCs); and • hybrid traction subsystem combining internal combustion engine and electric drive. Such combined energy sources and converters must be handled by energy management strategies (EMSs). In which, optimization-based methods are of interest due to their high performance. Nonetheless, these methods are often complicated and computation consuming which can be difficult to be realized in real-world applications. The objective of this thesis is to develop simple but effective real-time optimization-based EMSs for an electric car and a parallel hybrid truck supplied by batteries and SCs. The complexities of the studied system are tackled by using Energetic Macroscopic Representation (EMR) which helps to conduct reduced models for energy management at the supervisory level. Optimal control theory is then applied to these reduced models to accomplish real-time EMSs. These strategies are simple due to the suitable model reductions but systematic and high-performance due to the optimization-based methods. The performances of the proposed strategies are verified via simulations by comparing with off-line optimal benchmark deduced by dynamic programming. Moreover, real-time capabilities of these novel EMSs are validated via experiments by using reduced-scale power hardware-in-the-loop simulation. The results confirm the advantages of the proposed strategies developed by the unified approach in the thesis

Power sources coordination through multivariable LPV/Hinf control with application to multi-source electric vehicles

International audienceIn 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-inf 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-inf controller is also proposed to handle an embedded implementation with limited computational burden. The nonlinear multi-source system is simulated in MATLAB® / Simulink® 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

Energy Efficiency Comparison of Hybrid Powertrain Systems for Fuel-Cell-Based Electric Vehicles

Fuel cell electric vehicles have great superiorities in endurance mileage, charging speed and climate tolerance compared to battery electric vehicles. However, a supercapacitor or battery bank is required to maintain a fast-dynamic response, which leads to several hybridization structures for fuel-cell-based electric vehicles due to the unique characteristics of each device, and their performances are also differing. The purpose of this paper is to provide a comprehensive comparison of hybrid powertrain systems for three types of powertrains: fuel cell/supercapacitor passive hybrid, fuel cell/supercapacitor semi-active hybrid, and fuel cell/battery semi-active hybrid. Each powertrain component model is developed from the real components wherever possible, and Honda FCX Clarity fuel cell vehicle is studied as the benchmark. The powertrain energy efficiency under Worldwide harmonized Light vehicles Test Cycle (WLTC) is analyzed and evaluated. The simulation results show that three powertrains have the same energy consumption, and fuel cell/supercapacitor passive hybrid powertrain increases the system efficiency by 2% and 4% in propulsion and regenerative braking, respectively. By contrast, the other two powertrain topologies have similar performance in terms of energy efficiency

Control and Optimization of Fuel Cell Based Powertrain for Automotive Applications

Fuel cell powered electric vehicles, with fast-refueling time, high energy density, and zero CO2 emissions, are becoming a promising solution for future fossil-free transportation. However, the relatively slow dynamic response and the inability of recovering the regenerative energy make vehicles solely powered by fuel cells not an immediately attractive solution. Instead, hybrid vehicles powered by fuel cells combined with energy buffers such as batteries and supercapacitors could be of more interest. Due to the unique characteristics of each energy buffer, the vehicle performance may vary with the hybrid energy storage system configuration. This thesis performs a comprehensive study on various energy storage configurations for applications in fuel cell hybrid electric vehicles. This thesis first examines the fuel cell/supercapacitor passive hybrid configuration where the fuel cell and supercapacitor share the same DC-link voltage. The power distribution between them is inherently determined by their internal resistances. Therefore, the DC-link voltage varies and depends on the vehicle power demand. In this work, a fuel cell/supercapacitor passive hybrid powertrain is first modeled and evaluated. Simulation results show that the energy efficiency is 53%–71% during propulsion and 84%–94% during braking, respectively. Moreover, a 3 kW lab-scale fuel cell/supercapacitor passive hybrid system is designed and investigated. Experimental results show that the fuel cell takes time to respond to a load change, while the supercapacitor provides the transient power, which makes it possible to downsize the fuel cell.Since the passive configuration loses the active controllability, this thesis further considers a fully-active fuel cell/supercapacitor system to improve the controllability of the power distribution. This configuration requires a boost converter for the fuel cell and a buck-boost converter for the supercapacitor. In this work, an adaptive power split method is used to smooth the fuel cell current and prevent the supercapacitor from exceeding its lower and upper charge limits. The cut-off frequency of the low-pass filter is adaptively controlled by the spectrum area ratio. Experimental results show that the supercapacitor state-of-charge is effectively controlled within the desired range. Moreover, a load disturbance compensator is proposed and demonstrated to improve the control performance such that the DC-link voltage fluctuation caused by the load current variation is significantly reduced.This thesis also investigates the cost-effectiveness of different energy buffers hybridized with fuel cells in various trucking applications. First, a chance-constraint co-design optimization problem is formulated. Convex modeling steps are presented to show that the problem can be decomposed and solved using convex programming. Results show that the power rating of the electric machine can be dramatically reduced when the delivered power is satisfied in a probabilistic sense. Moreover, the hybridization of fuel cells with lithium-ion batteries results in the lowest cost while the vehicle using lithium-ion capacitors as the energy buffer can carry the heaviest payload. This work also develops a robust co-design optimization framework considering the uncertainties in parameters (e.g., vehicle movement) and design decision variables (e.g., scaling factors of fuel cells and batteries). Results show that these uncertainties might propagate to uncertainties in state variables (e.g., battery energy) and optimization variables (e.g., battery power), leading to a larger battery capacity and therefore a higher total cost in robust optimal solutions. In summary, this thesis performs a comprehensive study on control and optimization of fuel cell based powertrains for automotive applications. This will provide a guidance on component selection and sizing, as well as powertrain system configuration and optimization for design of fuel cell powered electric vehicles

Real-time backstepping control for fuel cell vehicle using supercapacitors

A key issue of real-time applications is ensuring the operation by taking into account the stability constraints. For multisource vehicles, stability is impacted by the multisource interactions. Backstepping control ensures stable control for most classes of nonlinear systems. Nevertheless, no backstepping control in real time has been yet proposed for multisource vehicles. The objective of this paper is to apply the backstepping control to a multisource vehicle with fuel cell and supercapacitors for real-time implementation. A distribution criterion is used to allocate energy between sources. Experimental results demonstrate that the developed backstepping control can be implemented in real-time conditions. The supercapacitors can thus help the fuel cell to meet the requirements of the load with a guarantee of system stability. © 1967-2012 IEEE

Energy Conversion and Control of Hydrogen Fuel Cell Based Electric Transport

The research investigates the effective utilization of hydrogen fuel cells in electric transport applications, addressing the challenges associated with power generation, energy storage, and control. By implementing the MPPT Perturb and Observe (P&O) technique, the thesis aims to optimize the power output of the fuel cell system, ensuring maximum efficiency and performance. To enhance the overall energy management of the system, a battery and supercapacitor combination is employed as supplementary energy storage. The thesis dives into the design and control strategies required for the seamless integration of these energy conversion systems. The battery’s SOC is closely regulated based on the fuel cell voltage, allowing for efficient energy utilization and improved system reliability. The findings of this research contribute to the advancement of hydrogen fuel cell based electric transport systems. The utilization of MPPT techniques, combined with the integration of battery and supercapacitor systems, offers a promising approach to optimize energy conversion and control. The proposed strategies can lead to enhanced energy efficiency, extended driving range, and improved reliability for future hydrogen fuel cell-based electric transport applications