Real time adaptive efficient cold start strategy for proton exchange membrane fuel cells

Cold start of proton exchange membrane fuel cells (PEMFCs) at sub-zero temperatures is perceived as one of the obstacles in their commercialization way in automotive application. This paper proposes a novel internal-based adaptive strategy for the cold start of PEMFC to control its operating current in real time in a way to maximize the generated heat flux and electrical power in a short time span. In this respect, firstly, an online parameter identification method is integrated into a semi-empirical model to cope with the PEMFC performances drifts during cold start. Subsequently, an optimization algorithm is launched to find the best operating points from the updated model. Finally, the determined operating point, which is the current corresponding to the maximum power, is applied to PEMFC to achieve a rapid cold start. It should be noted that the utilization of adaptive filters has escaped the attention of previous PEMFC cold start studies. The ultimate results of the proposed strategy are experimentally validated and compared to the most commonly used cold start strategies based on Potentiostatic and Galvanostatic modes. The experimental outcomes of the comparative study indicate the striking superior performance of the proposed strategy in terms of heating time and energy requirement. © 2018 Elsevier Lt

Investigating the impact of ageing and thermal management of a fuel cell system on energy management strategies

This paper studies the impact of two significant aspects, namely fuel cell (FC) degradation and thermal management, over the performance of an optimal and a rule-based energy management strategy (EMS) in a fuel cell hybrid electric vehicle (FCHEV). To do so, firstly, a vehicle's model is developed in simulation environment for a low-speed FCHEV composed of a FC stack and a battery pack. Subsequently, deterministic dynamic programming (DP), as an optimal strategy, and bounded load following strategy (BLFS), as a common rule-based strategy, are utilized to minimize the hydrogen consumption while respecting the operating constraints of the power sources. The performance of the EMSs is assessed at different scenarios. The first objective is to clarify the effect of FC stack degradation on the performance of the vehicle. In this regard, each EMS determines the required current from the FC stack for two FCs with different levels of degradation. The second objective is to evaluate the thermal management contribution to improving the performance of the new FC compared to the considered cases in scenario one. In this respect, each strategy deals with determining two control variables (FC current and cooling fan duty cycle). The results of this study indicate that negligence of adapting to the PEMFC health state, as the PEMFC gets aged, can increase the hydrogen consumption up to 24.8% in DP and 12.1% in BLFS. Moreover, the integration of temperature dimension into the EMS can diminish the hydrogen consumption by 4.1% and 5.3% in DP and BLFS respectively. © 2020 Elsevier Lt

Efficient model selection for real-time adaptive cold start strategy of a fuel cell system on vehicular applications

The PEMFC maximum power is greatly influenced by subfreezing temperature and degradation phenomena. Therefore, a dependable model is required to estimate the power with respect to the variation of the operating conditions and state of health. Semi-empirical models are potent tools in this regard. Nonetheless, there is not much information about their cold environment reliability. This paper comprehensively compares the performance of some models (already tested in normal ambient temperature) in subfreezing condition to introduce the most reliable one for PEMFC cold start-up application. Firstly, seven models are compared regarding voltage losses and precision. Subsequently, the three most dependable ones are selected and experimentally compared at sub-zero temperature in terms of polarization curve estimation for three PEMFCs with different degradation levels. The results of this study indicate that the model introduced by Amphlett et al. has a superior performance compared to other ones regarding the characteristic's estimation in below-zero temperature

Comparative analysis of two online identification algorithms in a fuel cell system

Output power of a fuel cell (FC) stack can be controlled through operating parameters (current, temperature, etc.) and is impacted by ageing and degradation. However, designing a complete FC model which includes the whole physical phenomena is very difficult owing to its multivariate nature. Hence, online identification of a FC model, which serves as a basis for global energy management of a fuel cell vehicle (FCV), is considerably important. In this paper, two well-known recursive algorithms are compared for online estimation of a multi-input semi-empirical FC model parameters. In this respect, firstly, a semi-empirical FC model is selected to reach a satisfactory compromise between computational time and physical meaning. Subsequently, the algorithms are explained and implemented to identify the parameters of the model. Finally, experimental results achieved by the algorithms are discussed and their robustness is investigated. The ultimate results of this experimental study indicate that the employed algorithms are highly applicable in coping with the problem of FC output power alteration, due to the uncertainties caused by degradation and operation condition variations, and these results can be utilized for designing a global energy management strategy in a FCV. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinhei

Operating cost comparison of a single-stack and a multi-stack hybrid fuel cell vehicle through an online hierarchical strategy

One of the recently suggested solutions for enhancing the fuel economy and lifetime in a fuel cell (FC) hybrid electric vehicle (HEV) is the use of a multi-stack (MS) structure for the FC system. However, to fully realize the potential of this structure, the design of an appropriate energy management strategy (EMS) is necessary. This paper aims to compare the operating cost, including hydrogen consumption and degradation of the FC, between a single-stack (SS) and an MSFC-HEV. To do so, a hierarchical EMS, composed of two layers, is devised for the MS system. In the first layer, a rule-based strategy determines how many FCs should be ON according to the requested power, battery state of charge (SOC), and FCs degradations. In the second layer, an equivalent consumption minimization strategy (ECMS) is developed to determine the output power of each activated FC according to the cost function and constraints. Regarding the SS structure, ECMS is employed for power distribution. The purpose of this strategy is to decrease fuel consumption and FC system degradation costs in both structures. The performance of the ECMS is compared with dynamic programming (DP) as a global optimization strategy for validation purposes. The obtained results using experimental data show that an FC-HEV with an MS structure reaches less hydrogen and degradation costs than an SS one

An online self cold startup methodology for PEM fuel cells in vehicular applications

This paper puts forward an adaptive cold start strategy for a proton exchange membrane fuel cell (PEMFC) based on maximum power mode. The proposed strategy consists of a water evacuation process after PEMFC shutdown and a self-heating process at PEMFC cold startup. To maximize the performance of the suggested strategy, an optimal operating condition for the cold start procedure is sought first. In this respect, an experimental parametric study is performed to explore the impact of fan velocity, micro-short circuit, anode pressure, and purge procedure on the PEMFC cold start performance. After laying down the proper conditions, the proposed cold start procedure is implemented on a test bench for experimental validations. The self-heating process is based on an online adaptive algorithm that maximizes the PEMFC's internal heat depending on its operating parameters' variation. In fact, this algorithm attempts to keep the current density at high levels, leading to PEMFC's performance improvement achieved by membrane hydration and temperature increase. The experimental results confirm the effectiveness of the proposed strategy, which presents a fast and cost-effective PEMFC's cold start. © 2020 IEEE

A decentralized multi-agent energy management strategy based on a look-ahead reinforcement learning approach

An energy management strategy (EMS) has an essential role in ameliorating the efficiency and lifetime of the powertrain components in a hybrid fuel cell vehicle (HFCV). The EMS of intelligent HFCVs is equipped with advanced data-driven techniques to efficiently distribute the power flow among the power sources, which have heterogeneous energetic characteristics. Decentralized EMSs provide higher modularity (plug and play) and reliability compared to the centralized data-driven strategies. Modularity is the specification that promotes the discovery of new components in a powertrain system without the need for reconfiguration. Hence, this article puts forward a decentralized reinforcement learning (Dec-RL) framework for designing an EMS in a heavy-duty HFCV. The studied powertrain is composed of two parallel fuel cell systems (FCSs) and a battery pack. The contribution of the suggested multi-agent approach lies in the development of a fully decentralized learning strategy composed of several connected local modules. The performance of the proposed approach is investigated through several simulations and experimental tests. The results indicate the advantage of the established Dec-RL control scheme in convergence speed and optimization criteria. © 2021 SAE International Journal of Electrified Vehicles

Effects of price range variation on optimal sizing and energy management performance of a hybrid fuel cell vehicle

Abstract: The usage of multi-objective cost functions (MOCFs) in sizing and energy management strategy (EMS) of fuel cell hybrid electric vehicles (FCHEVs) has expanded due to the participation of multiple technological and economic disciplines. To better understand the impact of price fluctuation on the component size and EMS of an FCHEV, this article proposed a sensitivity analysis methodology. First, a two-step optimization approach that considers hydrogen consumption, system degradation, and trip cost is used to minimize a MOCF of the Can-Am Spyder electric motorcycle simulator. Then, an effect analysis is carried out for the cost-optimal results under two driving profiles to understand the link between cost variation and system performance. These simulations indicate that each might result in different system sizes and EMS compromise. After that, an online optimization EMS based on sequential quadratic programming is used on a reduced-scale hardware-in-the-loop configuration to evaluate the simulation results with varied weights. Experimental results indicate that when an adequate size is used for each pair of weights, the EMS results in a 6% decrease in the trip cost

Passive and active coupling comparison of fuel cell and supercapacitor for a three-wheel electric vehicle

The desire to reduce the power electronics related issues has turned the attentions to passive coupling of powertrain components in fuel cell hybrid electric vehicles (FCHEVs). In the passive coupling, the fuel cell (FC) stack is directly connected to an energy storage system on the DC bus as opposed to the active configuration where a DC-DC converter couples the FC stack to the DC bus. This paper compares the use of passive and active couplings in a three-wheel FCHEV to reveal their strengths and weaknesses. In this respect, a passive configuration, using a FC stack and a supercapacitor, is suggested first through formulating a sizing problem. Subsequently, the components are connected in an active configuration where an optimized fuzzy energy management strategy is used to split the power between the components. The performance of the vehicle is compared at each case in terms of capital cost and trip cost, which is composed of FC degradation and hydrogen consumption, and total cost of the system per hour. The obtained results show the superior performance of the passive configuration by 17% in terms of total hourly cost, while the active one only results in less degradation rate in the FC system. © 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinhei