Fuel Cell Hybrid Vehicle Research Articles

Adaptive energy management strategy for fuel cell/battery hybrid vehicles using Pontryagin's Minimal Principle

The fuel cell hybrid vehicle provides an efficient and low-emission alternative for the internal combustion engine vehicle. The energy management strategy (EMS) commands the power split between the power sources and is crucial to the hybrid vehicles. In this work, we propose an adaptive EMS based on Pontryagin's Minimal Principle for a fuel cell/battery hybrid vehicle, in which the co-state adaptation is performed by driving cycle prediction. In order to improve the co-state estimation accuracy, an improved Markov based velocity prediction is proposed considering the driving behavior under different driving patterns. Moreover, the driving pattern is recognized online based on a support vector machine method, which is optimized by particle swarm optimization. We build a combined driving cycle to verify the effectiveness of the proposed strategy, simulation results under three cases show that the proposed strategy can foresee the driving behaviors and update the co-state reasonably. Comparing with the rule-based EMS, the proposed strategy achieves a better fuel economy with a hydrogen consumption reduction by 4% and a relatively low average power change rate of fuel cells. Moreover, it achieves a close performance to the offline optimal algorithms.

Exergoeconomic analysis and optimization of a new hybrid fuel cell vehicle

This paper introduces thermodynamic and economic analyses on a newly developed energy system for powering hybrid vehicles based on both energy and exergy concepts. The proposed hybrid propulsion system incorporates a liquefied ammonia tank, ammonia dissociation and separation unit (DSU), an internal combustion engine (ICE), and a fuel cell (FC) system. The exhaust gases released from the ICE are exploited to supply the necessary thermal energy to decompose ammonia thermally into hydrogen and nitrogen on board. The ICE is fuelled with a blend of ammonia and hydrogen generated from the DSU. The additional hydrogen released from the DSU will also be provided to the fuel cell system to run the FC and generate electric power, which will be supplied to the electric motor to provide the required traction to the vehicle. An optimization study is also performed to identify optimum design variables. The parametric studies are included in this investigation to evaluate the influence of varying the different operational parameters on the system energy and exergy efficiencies and both total cost rate and exergoeconomic factor values of the system.

Development of bi-directional DC/DC converter for fuel cell hybrid vehicle

Dual active full-bridge (DAB) DC/DC converters are widely used in energy storage systems with bidirectional energy flow, such as fuel cell hybrid vehicles. This paper presents a robustness design method for DAB converter power system stabilizers. Based on the single-phase-shift control model of the DAB converter, the small signal model and the multicell structure of the converter are established and the state equation of the system is obtained. Then, the controller design problem is transformed into a linear quadratic regulator problem, which is solved by linear matrix inequality. The controller designed by this method can make the DC/DC converter run stably even when the parameters are uncertain, which is verified by simulation and experiments.

Development of flexible procedures for co-optimizing design and control of fuel cell hybrid vehicles

Developing successful fuel cell hybrid vehicles (FCHVs), to be destined to the widest deployment within the entire transport sector, is nowadays considered as a highly strategic target to fully meet well known environmental and regulatory constraints at international level. This happens thanks to the intrinsic overall superior features of fuel cell propulsion when compared to both electric and hybrid vehicles, such as high fuel-economy, reduced tank-to-wheel environmental impact and good ranges. Successful achievement of the above-introduced challenging goal motivates the research activity presented and discussed in this paper, namely the development of an advanced mathematical tool featuring co-optimization capabilities. The reason for such a requirement lies in the well-known strong interactions and mutual influence between selected design criteria and adopted control strategies. Therefore, a comprehensive model of a generic FCHV architecture and a specification independent control strategy, thus adaptable to different fuel cell system and battery sizes, were preliminary developed. Then, they were integrated and embedded within a modular constrained optimization algorithm, which was conceived in such a way as to simultaneously find the optimal FCHV powertrain design, as well as real-time applicable control strategies. Suitable design and energy management criteria were investigated on a selected driving cycle, in such a way to explore several powertrain configurations (i.e. more hybrid, as well as more plugin and range-extender like FCHV). This allowed verifying the suitability of the proposed procedure to yield solutions ensuring low hydrogen consumption (i.e. fuel economy as high as 135 km/kg) and full alignment with targeted energy management policies. Discussion of results, together with the physical meaning of main design and control variables provided as outcomes, underline the effectiveness of the proposed tool in providing a solid support in the preliminary design of cost-effective fuel cell powertrains destined to a variety of applications and driving habits.

Techno-economic evaluation of a hybrid fuel cell vehicle with on-board MeOH-to-H2 processor

A new on-board MeOH-to-H2 processor, which is a combination of multi-tube annular membrane methanol reformer (MTAMMR), plate-fin heat exchangers, fuel tank, and auxiliary equipment, is installed into the hybrid fuel cell vehicle named as the methanol reformer-based hybrid fuel cell (MRHFC) vehicle. Compared to the high-pressure hydrogen tank in the direct hydrogen fuel cell (DHHFC) vehicle, e.g. 2016 Toyota Mirai hybrid fuel cell vehicle, we found that (i) the estimated size of the MeOH-to-H2 processor is smaller than that of the hydrogen tank by 46.6% if the sizes of auxiliary equipment are not taken into account, and (ii) the estimated capital cost of the stainless steel MeOH-to-H2 processor is lower than that of the hydrogen tank by 77% if the present high cost of the tubular membrane is ignored. To explore the fuel economy of the MRHFC vehicle with different batteries, the urban/highway driving cycles in terms of the acceleration performance and the hybrid ratio (HR) of battery power and motor peak power is investigated by an advanced vehicle simulator (ADVISOR). The simulations show that (i) the high HR can reduce the total cost as well as increase the fuel economy of the MRHFC vehicle, and (ii) the Li-ion battery is better equipped to ensure the high fuel economy and avoid the undesired state of charge (SOC) of battery while HR = 0.6.

Modular Regenerative Emulation System for DC–DC Converters in Hybrid Fuel Cell Vehicle Applications

This paper proposes a novel emulation system for emulating the power system in the fuel cell electric vehicle. The major purpose of the proposed emulation system is to test the dc-dc converter between the fuel cell and high-voltage powertrain. The bidirectional buck-boost type dc-dc converter is applied in the emulation system as the basic elements. A modularized approach is presented for easily scaling up and down the power level of the emulation system. Meanwhile, an energy loop structure is implemented in the proposed emulation system for power capability boosting purpose. Because of the proposed energy loop configuration, the emulation system offers long-term running capability with high power rating without the grid connection. A neutral current control mechanism is applied in this paper to further enhance the long-term testing capability as well as extending the lifespan for the battery packages. The simulation studies are proposed in this paper to validate the control mechanisms of the emulation system. A 10 kW hardware prototype has been built and the experimental tests are presented for validating the functionalities of the emulation system.

Modelling and predicting energy consumption of a range extender fuel cell hybrid vehicle

Energy consumption is an important economical index of a fuel cell hybrid vehicle (FCHV). To analyse the energy consumption of a range extender FCHV and reduce the cost of experiments, this study developed a nonlinear regression model of the powertrain of the vehicle to predict the current and voltage on the DC bus, which were used in the investigation of energy consumption, by using the intelligent algorithms including Back Propagation neural network (BP), Genetic Algorithm-Back Propagation neural network (GABP) and least square support vector machine (LSSVM). The model based on the LSSVM achieves the best predicted performance and can consider the nonlinear characteristics of the powertrain quite well. A case study was discussed by applying the obtained model and integrated with a hierarchical energy management strategy (HEMS). The specific results of energy consumption showed that it is feasible to use the predicted data of the obtained model in the analysis of the energy consumption of the FCHV.

Mehrdad Ehsani, Yimin Gao, Stefano Longo and Kambiz M. Ebrahimi: Modern Electric Hybrid Electric and Fuel Cell Vehicles (3rd Edn)

Mehrdad Ehsani, Yimin Gao, Stefano Longo and Kambiz M. Ebrahimi: Modern Electric Hybrid Electric and Fuel Cell Vehicles (3rd Edn)

Dynamic analysis of a PEM fuel cell hybrid system with an on-board dimethyl ether (DME) steam reformer (SR)

Low-temperature polymer electrolyte membrane fuel cell (PEMFC) acts as a promising energy source due to the non-pollution and high-energy density. However, as hydrogen supply is a major constraint limiting the wide spread of fuel cell vehicles, a dimethyl ether (DME)-steam on-board reformer (SR) based on catalytic reforming via a catalytic membrane reactor with a channel structure is a possible solution to a direct hydrogen supply. The DME-SR reaction scheme and kinetics in the presence of a catalyst of CuO/ZnO/Al2O3+ZSM-5 are functions of the temperature and hydrocarbon ratio in the hydrogen-reforming reaction. An electric heater is provided to keep the temperature at a demanded value to produce hydrogen. As there is no available analysis tool for the fuel cell battery hybrid vehicle with on-board DME reformer, it is necessary to develop the tool to study the dynamic characteristics of the whole system. Matlab/Simulink is utilized as a dynamic simulation tool for obtaining the hydrogen production and the power distribution to the fuel cell. The model includes the effects of the fuel flow rate, the catalyst porosity, and the thermal conductivity of different subsystems. A fuel cell model with a battery as a secondary energy storage is built to validate the possible utilization of on-board reformer/fuel cell hybrid vehicle. In consideration of time-delay characteristic of the chemical reactions, the time constant obtained from the experiment is utilized for obtaining dynamic characteristics. The hydrogen supplied by the reformer and the hydrogen consumed in the PEMFC prove that DME reformer can supply the adequate hydrogen to the fuel cell hybrid vehicle to cope with the required power demands.

A Fuel Cell Hybrid Vehicle Powertrain Emulator: Energy Management and Experimental Analysis

In this paper, a fuel cell hybrid vehicle powertrain emulator is proposed as a feasible test bench for validating energy management strategies. Firstly, the configuration and structure of the emulator is briefly presented, and a fuel cell and lithium-ion battery hybrid vehicle model based on the data obtained from a real fuel cell-battery hybrid light electric vehicle is used for testing the stability of the emulator. The comparative experiment demonstrates a power simulation error of 3.848%. Secondly, a fuzzy logic algorithm-based energy management strategy was implemented on the emulator with an objective of optimizing the energy distribution between the fuel cell stack and battery pack via the corresponding rules and membership functions. Finally, an experiment test embedded the energy management strategy on the emulator is carried out during the urban dynamometer driving schedule (UDDS) cycle. And the results indicate that the fuel cell stack works primarily in low-load and constant driving conditions. Meanwhile, the battery pack supplies the dynamic instantaneous power to meet the power requirements during high-load conditions. It is fully consistent with the proposed energy management strategy. That is, the proposed emulator is a reliable platform for further energy management research.

Optimization of Hydrogen Consumption for fuel cell hybrid vehicle

Objective: To minimize the hydrogen consumption in hybrid fuel cell/super capacitor vehicle tested with a proposed energy management. Methods: The studied system consists of two energy sources: namely Proton Exchange Membrane (PEM) Fuel Cell and a super capacitor. So we propose a new architecture system controlled through a proposed energy flow management approach which determines the power demand between the PEM fuel cell, super capacitor and the load. Findings: The control strategy tested with the different driving cycle’s exhibit excellent performance in order to minimize the hydrogen consumption. A simulation model for the power train proposed is simulated and tested by using Matlab/ Simulink software, in order to verify the efficiency of our proposed approach. Applications: This work will be followed by implementing the proposed system on an embedded electronic board such us FPGAs, STM32s. Keywords: Energy Management, Hydrogen Consumption, Hybrid Vehicle, PEM Fuel Cell, Power Train, Super Capacitor

Fuel Cell Power Train System Simulation of a Car SAMAND SOREN

Due to increasing energy crisis and environmental problems because of air pollution, fuel cell hybrid vehicles are considered as an alternative for internal combustion (IC) vehicles. Proton exchange membrane fuel cells (PEMFC) are the most proper kind of fuel cells for portable usage due to high power density and low performance temperature. In this paper, power train system of a real car, SAMAND SOREN, is modeled and simulated using a dynamic model in MATLAB/SIMULINK software. Five important subsystems in the model are: cathode air supply system, anode fuel supply system, electric motor, battery, and power transmission system. Finally, parameters like power and voltage produced by fuel cell, electric motor torque and vehicle speed are demonstrated as results.

Minimum time current controller design for two-interleaved bidirectional converter: Application to hybrid fuel cell/supercapacitor vehicles

In fuel cell hybrid vehicles (FCHV) with a supercapacitor (SC) used as auxiliary source of hybridization, classical SC converters limit the current tracking performance due to the presence of a large input inductance. A hardware solution to this issue consists in using an interleaved converter topology that enables considerably reducing the input inductance. To optimize interleaved converters usage, an intelligent control scheme that maximizes closed-loop performance in current tracking must be designed. For that purpose, we design two controllers: a transient-state controller and a steady-state one. The first controller is a bang-bang one that guaranties a fast transition from the initial condition to some closed region around the reference. The second controller ensures the local asymptotic stabilization of a certain desired limit cycle and is based on switching surfaces design. The proposed control scheme performances and robustness are evaluated through simulations with piece-wise constant source and reference current. Performances are also evaluated on a battery-like supercapacitor vehicle using an urban driving cycle.

A combinatorial optimisation approach to energy management strategy for a hybrid fuel cell vehicle

Hybrid Electric Vehicles are becoming more and more prevalent for economic and environmental reasons. Many studies have been conducted in order to improve Hybrid Electric Vehicle performance by increasing their autonomy while respecting the power demand of the electric motor and various constraints. Focusing on the Hybrid Electric Vehicle energy management problem, different approaches and strategies already exist based on non-linear modelling, selection of adequate architecture and source design or the expertise of the manufacturer in the domain. In this paper, a new combinatorial approach is presented to optimally manage offline Hybrid Electric Vehicle energy distribution, composed of two energy sources: a fuel cell as a main source and a super-capacitor for energy storage. New mathematical modelling has been developed that reflects the functioning of the Hybrid Electric Vehicle energy chain, using an exact method to provide an optimal solution that corresponds to hydrogen consumption. Simulations were performed on different realistic mission profiles that showed a significant gain in solution quality and computation time compared with other approaches presented in the literature. Since the quality of solutions depends on the reliability of input data, including disruptions, a robustness study also is carried out.

Study of the energy performance of a PEM fuel cell vehicle

This paper presents the Performance of Proton Exchange Membrane Fuel Cell (PEMFC).If the need of the individual transport is growing; the methods proposed are strongly questioned by the society. Emissions from combustion engines are accused of contributing to global warming and air pollution. In addition, the oil resources are finite while demand increases inevitably based on economic growth (31% of global energy consumption for transportation sector). So, an alternative to the combustion engine becomes essential. The hybrid fuel cell vehicle represents one of the alternatives solutions. The present work is a numerical simulation of the energy performance of a PEMFC fuel cell vehicle rolling on a driving reference cycle (FTP cycle). The simulations are conducted and performed with the ADVISOR simulation tool using the MATLAB environment. The results concerning the battery power, fuel cell power and the thermal state of the battery show a very candidate of this vehicle to replace the conventional engine.

Energy management strategy for a fuel cell hybrid vehicle based on maximum efficiency and maximum power identification

This paper addresses the energy management strategy (EMS) for a fuel cell hybrid electric vehicle (FC-HEV). The fuel cell system (FCS) is a multi-physics system, and consequently, its energetic performances depend on the degradation and on the operating conditions. The maximum power (MP) and the maximum efficiency (ME) points of the FCS are unique but they move with operating condition variations. Thus, developing an extremum seeking process (ESP) for both MP and ME tracking is a challenging task. In the ESP, models are identified online by using an adaptive recursive least square (ARLS) method to seek a variation in the FCS performances. Then an optimisation algorithm is used on the updated model to find the MP and the ME points. The ESP is incorporated into a hysteresis power splitting control (HPSC). A MP mode or a ME mode can be set based on the energy storage level (battery pack). The effectiveness of the proposed MP- and ME-ESP EMS is demonstrated by conducting experimental studies on two FCSs with different levels of degradation. It was demonstrated that the classical EMS based on maps are not valid when the operating parameters vary because of the level of degradation change.

Multi-objective energy management optimization and parameter sizing for proton exchange membrane hybrid fuel cell vehicles

The powertrain system of a typical proton electrolyte membrane hybrid fuel cell vehicle contains a lithium battery package and a fuel cell stack. A multi-objective optimization for this powertrain system of a passenger car, taking account of fuel economy and system durability, is discussed in this paper. Based on an analysis of the optimum results obtained by dynamic programming, a soft-run strategy was proposed for real-time and multi-objective control algorithm design. The soft-run strategy was optimized by taking lithium battery size into consideration, and implemented using two real-time algorithms. When compared with the optimized dynamic programming results, the power demand-based control method proved more suitable for powertrain systems equipped with larger capacity batteries, while the state of charge based control method proved superior in other cases. On this basis, the life cycle cost was optimized by considering both lithium battery size and equivalent hydrogen consumption. The battery capacity selection proved more flexible, when powertrain systems are equipped with larger capacity batteries. Finally, the algorithm has been validated in a fuel cell city bus. It gets a good balance of fuel economy and system durability in a three months demonstration operation.

Sizing for fuel cell/supercapacitor hybrid vehicles based on stochastic driving cycles

In this article, a methodology for the sizing and analysis of fuel cell/supercapacitor hybrid vehicles is presented. The proposed sizing methodology is based on the fulfilment of power requirements, including sustained speed tests and stochastic driving cycles. The procedure to generate driving cycles is also presented in this paper. The sizing algorithm explicitly accounts for the Equivalent Consumption Minimization Strategy (ECMS). The performance is compared with optimal consumption, which is found using an off-line strategy via Dynamic Programming. The sizing methodology provides guidance for sizing the fuel cell and the supercapacitor number. The results also include analysis on oversizing the fuel cell and varying the parameters of the energy management strategy. The simulation results highlight the importance of integrating sizing and energy management into fuel cell hybrid vehicles.

Co-state variable determination in Pontryagin’s Minimum Principle for energy management of hybrid vehicles

In order to achieve the best fuel economy for hybrid vehicles, energy management strategies should optimize the power allocation between power sources. Recently, Pontryagin’s Minimum Principle (PMP) has been attracting attention for the energy management of hybrid vehicles owing to the solution optimality and the calculation instantaneity. In the PMP, there is an important control parameter, which is defined as the co-state variable and difficult to be determined. This research mainly deals with the co-state variable, where the PMP is applied to a fuel cell hybrid vehicle (FCHV) and a hybrid electric vehicle (HEV) respectively, and the effect of the co-state variable on the optimal solution is discussed for each case. The determination of the co-state variable for the cases of certain driving cycles and uncertain driving cycles is discussed, and an online co-state variable updating method is proposed for the uncertain driving cycle cases and its effectiveness is proved.

Research on hybrid ratio of fuel cell hybrid vehicle based on ADVISOR

In order to improve the work coordination of powertrain of fuel cell hybrid vehicle and solve the problems of vehicle dynamic performance and fuel economy, the main components of powertrain were selected for hydrogen-oxygen proton exchange membrane fuel cell-lead acid battery hybrid vehicle. Then some feasible power matching schemes of fuel cell and lead-acid battery were determined. At last the vehicle simulation platform in ADVISOR was established and all sorts of matching schemes in FTP and ECE_EUDC simulation conditions were simulated. To meet the requirements of vehicle dynamic performance, fuel economies of all sorts of matching schemes were analyzed, and the best match of fuel cell and lead acid battery was obtained.