Design of Energy Management System of a PEMFC–Battery– Supercapacitor Hybrid Tramway

In this chapter, a hybrid power system that consists of multiple proton exchange membrane fuel cell (PEMFC) systems, batteries, and supercapacitors (SCs) is developed for a hybrid tramway. Three energy management strategies that included a fuzzy logic control (FLC), an equivalent consumption minimization strategy (ECMS), and a state machine strategy based on droop control (SMS-DC) are utilized to coordinate multiple power sources, avoid the transients and rapid changes of power demand, and achieve high efficiency without degrading the mechanism performance for an energy management system of hybrid tramway. A hybrid system model of tramway is established with commercially available devices, and then the different energy management strategies are evaluated with a real driving cycle of tramway from Turkey. The results compared with these strategies demonstrate that the higher average efficiencies of the tramway, the lower tramway-equivalent hydrogen consumptions, and more efficient use of the batteries and SCs energy are achieved by the SMS-DC. Therefore, the appropriate energy management system for high-power hybrid tramway will improve the hydrogen consumptions of overall hybrid system and the efficiencies of each power source

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

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

An adaptive power split strategy with a load disturbance compensator for fuel cell/supercapacitor powertrains

Electric vehicles powered by fuel cell and supercapacitor hybrid power sources are of great interest. However, the power allocation between each power source is challenging and the DC bus voltage fluctuation is relatively significant in cascaded PI control schemes. This paper develops a power control strategy with an adjustable cut-off frequency, using an artificial potential field, to adaptively split the load current between the fuel cell and the supercapacitor under various load conditions. The adaptive cut-off frequency is calculated by cutting the load frequency spectrum with an allocation ratio that changes with the supercapacitor state of charge. Therefore, the relatively lower frequency portion of the load current is provided by the fuel cell and the supercapacitor handles the higher frequency portion. To enhance the control performance of the DC bus voltage regulation against the load disturbance, a load disturbance compensator is introduced to suppress the DC bus voltage fluctuation when the load variation occurs, which is implemented by a feed-forward controller that can compensate the load current variation in advance. The effectiveness of the proposed strategy is validated by extensive experiments

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

Insights for Industry 4.0 Applications into a Hydrogen Advanced Mobility

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Energy management strategies for fuel cell vehicles: A comprehensive review of the latest progress in modeling, strategies, and future prospects

Fuel cell vehicles (FCVs) are considered a promising solution for reducing emissions caused by the transportation sector. An energy management strategy (EMS) is undeniably essential in increasing hydrogen economy, component lifetime, and driving range. While the existing EMSs provide a range of performance levels, they suffer from significant shortcomings in robustness, durability, and adaptability, which prohibit the FCV from reaching its full potential in the vehicle industry. After introducing the fundamental EMS problem, this review article provides a detailed description of the FCV powertrain system modeling, including typical modeling, degradation modeling, and thermal modeling, for designing an EMS. Subsequently, an in-depth analysis of various EMS evolutions, including rule-based and optimization-based, is carried out, along with a thorough review of the recent advances. Unlike similar studies, this paper mainly highlights the significance of the latest contributions, such as advanced control theories, optimization algorithms, artificial intelligence (AI), and multi-stack fuel cell systems (MFCSs). Afterward, the verification methods of EMSs are classified and summarized. Ultimately, this work illuminates future research directions and prospects from multi-disciplinary standpoints for the first time. The overarching goal of this work is to stimulate more innovative thoughts and solutions for improving the operational performance, efficiency, and safety of FCV powertrains

A novel energy management strategy for fuel-cell/supercapacitor hybrid vehicles

Hybrid platforms powered by fuel cell and supercapacitor represent a powertrain with active state-dependent constraints, providing an adverse scenario for the energy management. In these platforms, the performance of the vehicle in terms of efficiency and power compliance is noticeably affected by the energy management strategy. This paper presents a novel energy management strategy based on the estimation of the future energy demand. The strategy aims for maintaining the state of energy of the supercapacitor between two limits, which are computed online using the states of the system. The performance of the proposed strategy is tested by simulation in a hybrid electric bus operated under real urban driving conditions. The results show improvements on hydrogen consumption and on power compliance compared to the widely reported Equivalent Consumption Minimization Strategy. Also, the results include the comparison with the optimal strategy obtained offline through Dynamic Programming.Postprint (published version

Hybrid power management for fuel cell-supercapacitor powered hybrid electric vehicle

Fuel cell (FC) with a combination of supercapacitor (SC) based hybrid electric vehicles have been regarded as a potential solution in the future transportation system. This is due to their zero-emission, enhancement of transient power demand, ability to absorb the energy from the regenerative braking, high efficiency, and long mileage. Nevertheless, the nonlinear output characteristics of the FC system are a feeble point owing to internal constraints such as membrane water content and cell temperature. Hence it is essential to extricate as much power as possible from the stack to avert excessive fuel usage and low system efficiency. Conversely, despite the advantages of the SC as an auxiliary energy storage system, the series connection of SC cells causes a cell imbalance problem due to uneven cell characteristics that occur during the manufacturing process and its ambient conditions. This discrepancy of cell voltages in a supercapacitor module leads to reduce the stack’s efficiency and its lifetime. Furthermore, the above limitations of the power sources and initial state of SC’s charge affect the power management’s distribution of power among the multiple sources. Therefore, the aim of this thesis is to propose a hybrid power management for fuel cell-supercapacitor powered hybrid electric vehicles to solve the three identified problems. Firstly, this thesis focuses on a maximum power point tracking (MPPT) controller with a modified 4-leg interleaved boost converter (M-FLIBC) topology for the FC system. The effectiveness of the proposed IBC with a controller for the FC is compared with the two additional controllers couples with the conventional FLIBC topology. Next, a global modular balancer for voltage balancing of multiple supercapacitor cells is connected in series for an HEV system. The global modular balancing architecture is proposed based on forward conversion, which integrates cell balancing, module balancing, and operating for different frequencies. Thus, greatly reducing the volume and implementation complexity. Finally, the thesis evaluates hybrid power management (HPM) for effective power sources distribution, in order to reduce hydrogen consumption and enhance the vehicle's fuel economy. In this case, an equivalent circuit model of SC is developed for the energy storage system. The combination of an extended Kalman filter (EKF) and traditional coulomb counting (CC) method is used to estimate the SC state of charge in improving the effectiveness of the HPM. To evaluate the fuel economy under realistic driving conditions, the combined environmental protection agency (EPA) test cycles for a city and highway are considered. The outcome of performance comparison of the different controllers based on MPPT technique in terms of voltage, current, power, settling time, and efficiency of the FC indicates that the radial basis function network (RBFN) based MPPT controller with the M-FLIBC outperforms the PID and Fuzzy based controllers. With respect to controlling of SC in HEV environment, the proposed topology of SC presents effective voltage balancing with a lower component count, able to operate at different frequencies, i.e., 10 to 70 kHz, as well opens to unlimited stackable modular numbers of SC cells for the HEV performance analysis. Ultimately, with all the proposed control topologies and combined EKF-CC based power management for the FC-SC in Series HEV, the vehicle's fuel economy is increased to 93.38 km/kg as compared to traditional CC based power management of 86.53 km/kg, besides it improves the vehicle’s acceleration within 0-100 km/h in 9.0 seconds respectively. Finally, the research shows that the hybrid power management of FC and SC powered HEV leads to improved performance of the vehicle in terms of the key measures. Suggestions for future research are also highlighted