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

Topological analysis of powertrains for refusecollecting vehicles based on real routes – Part II: Hybrid electric powertrain

In this two-part paper, a topological analysis of powertrains for refuse-collecting vehicles (RCVs) based on simulation of different architectures (internal combustion engine, hybrid electric, and hybrid hydraulic) on real routes is proposed. In this second part, three different hybrid electric powertrain architectures are proposed and modeled. These architectures are based on the use of fuel cells, ultracapacitors, and batteries. A calculation engine, which is specifically designed to estimate energy consumption, respecting the original performance as the original internal combustion engine (ICE), is presented and used for simulations and component sizing. Finally, the overall performance of the different architectures (hybrid hydraulic, taken from the first paper part, and hybrid electric, estimated in this second part) and control strategies are summarized in a fuel and energy consumption table. Based on this table, an analysis of the different architecture performance results is carried out. From this analysis, a technological evolution of these vehicles in the medium- and long terms is proposed.Postprint (author's final draft

MIMO Hinf control for power source coordination - application to energy management systems of electric vehicles

International audienceThis paper deals with a control strategy used for designing energy management systems within average-power electric vehicles. The power supply system is composed of three sources, namely a fuel cell, a battery and an ultracapacitor - specialized within distinct frequency ranges - which must be coordinated in order to satisfy power demand of the vehicle's electrical motor. The three sources with their associated DC-DC converters are paralleled on a common DC-bus supplying the electrical motor. The DC-bus is required to be constant regardless of the load state thanks to the fuel cell which provides the mean power and to the other two sources - auxiliary sources - which are controlled to supply the high-frequency variations of power demand according to an H1 optimization strategy. MATLAB/ Simulink numerical simulation is used to validate the proposed strategy under real driving cycle condition proposed by IFSTTAR (Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux), and this approach is assessed against another optimal strategy that uses LQR as control design

Ultracapacitor Heavy Hybrid Vehicle: Model Predictive Control Using Future Information to Improve Fuel Consumption

This research is concerned with the improvement in the fuel economy of heavy transport vehicles through the use of high power ultracapacitors in a mild hybrid electric vehicle platform. Previous work has shown the potential for up to 15% improvement on a hybrid SUV platform, but preliminary simulations have shown the potential improvement for larger vehicles is much higher. Based on vehicle modeling information from the high fidelity, forward-looking modeling and simulation program Powertrain Systems Analysis Toolkit (PSAT), a mild parallel heavy ultracapacitor hybrid electric vehicle model is developed and validated to known vehicle performance measures. The vehicle is hybridized using a 75kW motor and small energy storage ultracapacitor pack of 56 Farads at 145 Volts. Among all hybridizing energy storage technologies, ultracapacitors pack extraordinary power capability, cycle lifetime, and ruggedness and as such are well suited to reducing the large power transients of a heavy vehicle. The control challenge is to effectively manage the very small energy buffer (a few hundred Watt-hours) the ultracapacitors provide to maximize the potential fuel economy. The optimal control technique of Dynamic Programming is first used on the vehicle model to obtain the \u27best possible\u27 fuel economy for the vehicle over the driving cycles. A variety of energy storage parameters are investigated to aid in determining the best ultracapacitor system characteristics and the resulting effects this has on the fuel economy. On a real vehicle, the Dynamic Programming method is not very useful since it is computationally demanding and requires predetermined vehicle torque demands to carry out the optimization. The Model Predictive Control (MPC) method is an optimization-based receding horizon control strategy which has shown potential as a powertrain control strategy in hybrid vehicles. An MPC strategy is developed for the hybrid vehicle based on an exponential decay torque prediction method which can achieve near-optimal fuel consumption even for very short prediction horizon lengths of a few seconds. A critical part of the MPC method which can greatly affect the overall control performance is that of the prediction model. The use of telematic based \u27future information\u27 to aid in the MPC prediction method is also investigated. Three types of future information currently obtainable from vehicle telematic technologies are speed limits, traffic conditions, and traffic signals, all of which have been incorporated to improve the vehicle fuel economy

Enhancing Performance of Hybrid Electric Vehicle using Optimized Energy Management Methodology

The fuel consumption and the fuel management strategy (PMS) of the hybrid electric vehicle are closely linked (HEV). In this study, a hybrid power management technique and an adaptive neuro-fuzzy inference (ANFIS) method are established. Artificial intelligence represents a huge improvement in electricity management across different energy sources (AI). The main energy source of the hybrid power supply is a proton exchange membrane fuel cell (PEMFC), while its electrical storage devices are a battery bank and an ultracapacitor. The hybrid electric vehicle's power management strategy (PMS) and fuel consumption are closely related (HEV). In this paper, an adaptive neuro-fuzzy inference and hybrid power management strategy (ANFIS) approach is developed. A significant advance in electricity management across multiple energy sources is artificial intelligence (AI). The proton exchange membrane fuel cell (PEMFC) serves as the primary energy source of the hybrid power supply, and the ultracapacitor and battery bank serve as its electrical storage components

A Parallel Energy-Sharing Control Strategy for Fuel Cell Hybrid Vehicle

This paper presents a parallel energy-sharing control strategy for the application of fuel cell hybrid vehicles (FCHVs). The hybrid source discussed consists of a fuel cells (FCs) generator and energy storage units (ESUs) which composed by the battery and ultracapacitor (UC) modules. A direct current (DC) bus is used to interface between the energy sources and the electric vehicles (EV) propulsion system (loads). Energy sources are connected to the DC bus using of power electronics converters. A total of six control loops are designed in the supervisory system in order to regulate the DC bus voltage, control of current flow and to monitor the state of charge (SOC) of each energy storage device at the same time. Proportional plus integral (PI) controllers are employed to regulate the output from each control loop referring to their reference signals. The proposed energy control system is simulated in MATLAB/Simulink environment. Results indicated that the proposed parallel energy-sharing control system is capable to provide a practical hybrid vehicle in respond to the vehicle traction response and avoids the FC and battery from overstressed at the same time.

Design and performance analysis of electric vehicles fed by multiple fuel cells

Recent advances in fuel cell developments have introduced them to many applications such as hybrid electric vehicles and heat/power cogenerations. They bring the advantage of clean energy and decrease the dependency on imported oil by providing fuel efficient devices in many applications such as electric vehicles. Conventional designs of hybrid fuel cell vehicles make use of a single fuel cell power source and a storage device to provide the base load and transients in various driving cycles. This thesis proposes a new configuration of multiple fuel cell power sources in hybrid fuel cell vehicles. Fuel cells are downsized in this new configuration to provide the same amount of power, which brings the advantage of a highly fuel economic design. The power control algorithm for this new configuration is presented and simulation results are studied for a case of double fuel cell power sources. Efficiency analysis for this new configuration is presented and compared with the conventional configuration. The main objective of this thesis is to achieve a higher efficiency in urban driving cycle. In conventional configurations, the fuel cell is not efficiently loaded in urban driving cycles, where small powers were required from the single fuel cell power source. Reliability analysis is also presented for this configuration

Energy Storage Systems for Traction and Renewable Energy Applications

Energy storage systems are the set of technologies used to store various forms of energy, and by necessity, can be discharged. Energy storage technologies have a wide range of characteristics and specifications. Like any other technology, each type of energy storage has its pros and cons. Depending on the application, it is crucial to perform a tradeoff study between the various energy storage options to choose the optimal solution based on the key performance objectives and various aspects of those technologies. The purpose of this thesis is to present a thorough literature review of the various energy storage options highlighting the key tradeoffs involved. This thesis focuses on evaluating energy storage options for traction and renewable energy applicationsHybrid Electric Vehicles (HEVs) is one key application space driving breakthroughs in energy storage technologies. The focus though has been typically on using one type of energy storage systems. This thesis investigates the impact of combining several types of batteries with ultracapacitor. A case study of integrating two energy storage systems in a series-parallel hybrid electric vehicle is simulated by using MATLAB-SIMULINK software.The other key application space is renewable energy especially wind and solar. Due to the intermittent nature of renewable energy sources, energy storage is a must to achieve the required power quality. Therefore, this thesis aims to investigate different cases of combining different types of energy storage with wind and solar. Hybrid Optimization Model for Electric Renewables (HOMER) software is utilized to study the economic and sizing aspects in each case

Urban and extra-urban hybrid vehicles: a technological review

Pollution derived from transportation systems is a worldwide, timelier issue than ever. The abatement actions of harmful substances in the air are on the agenda and they are necessary today to safeguard our welfare and that of the planet. Environmental pollution in large cities is approximately 20% due to the transportation system. In addition, private traffic contributes greatly to city pollution. Further, “vehicle operating life” is most often exceeded and vehicle emissions do not comply with European antipollution standards. It becomes mandatory to find a solution that respects the environment and, realize an appropriate transportation service to the customers. New technologies related to hybrid –electric engines are making great strides in reducing emissions, and the funds allocated by public authorities should be addressed. In addition, the use (implementation) of new technologies is also convenient from an economic point of view. In fact, by implementing the use of hybrid vehicles, fuel consumption can be reduced. The different hybrid configurations presented refer to such a series architecture, developed by the researchers and Research and Development groups. Regarding energy flows, different strategy logic or vehicle management units have been illustrated. Various configurations and vehicles were studied by simulating different driving cycles, both European approval and homologation and customer ones (typically municipal and university). The simulations have provided guidance on the optimal proposed configuration and information on the component to be used