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In this paper, the control strategy of a fully-active hybrid energy storage system, which uses two bi-directional DC/DC converters to decouple supercapacitor and battery pack from the DC bus, is proposed based on a 5th-order averaged model. Three control objectives, the battery and supercapacitor currents as well as the DC bus voltage, are regulated by using the two DC/DC converters. A Lyapunov-function-based controller is proposed to regulate the DC bus voltage to its reference value. In addition, a sliding-mode controller is designed to control the battery and supercapacitor currents to their reference values. The battery current reference is generated by the energy management strategy, while the supercapacitor current reference is generated by the Lyapunov controller to ensure DC bus voltage regulation. Simulation and experimental results show that the proposed control method has satisfactory performance, including robust tracking and a smooth transition when the load power varies in the large range.

This paper describes a hybrid tram powered by a Proton Exchange Membrane (PEM) fuel cell (FC) stack supported by an energy storage system (ESS) composed of a Li-ion battery (LB) pack and an ultra-capacitor (UC) pack. This configuration allows the tram to operate without grid connection. The hybrid tram with its full load is tested in the CRRC Qingdao Sifang Co.; Ltd. It firstly works on the operation mode switching method (OPMS) without energy regenerative and proper power management. Therefore, an equivalent consumption minimization strategy (ECMS) aimed at minimizing the hydrogen consumption is proposed to improve the characteristics of the tram. The results show that the proposed control system enhances drivability and economy, and is effective for application to this hybrid system.

Recently, there has been rapid development in the field of proton exchange membrane fuel cell (PEMFC) systems for transportation applications. The performance of a PEMFC system is very sensitive to the operating conditions, and uncontrolled working conditions may cause malfunctions and degradation. A robust control strategy is urgently needed, in order to improve the reliability of PEMFCs and prolong their working lifetime. To develop such a control strategy, one needs to not only model the system with identified parameters, but also know their uncertainties. In most studies related to system uncertainties, however, the parameter uncertainty is usually regarded as a pre-known condition. This paper proposes a method to identify key parameters and their boundaries of PEMFCs, and analyze the uncertainties of internal states based on Monte Carlo simulation. A nonlinear isothermal dynamic model, which takes into account the filling-and-emptying dynamic sub-models and a sub-model of mass transport through the membrane, is firstly introduced. Key parameters are then extracted stepwise using a nonlinear least squares (NLS) algorithm, and the parameter boundaries are identified based on Monte Carlo simulations. The uncertainties of internal states in time and frequency domains are investigated afterwards. The results demonstrate the effectiveness of this method. Among the three sub-systems (cathode, anode, and membrane), the cathode sub-system was found to have the smallest uncertainties, while the membrane has the largest. Transfer functions for small disturbances of cell current to the internal states also have uncertainties, which can be low-frequency pass or bandpass functions depending on the parameter values. Further study will focus on the design of robust control strategies based on system models with uncertainties.

Massive data storage is an advanced function in a fully functional battery management system (BMS). Reducing the recording signal length undoubtedly saves the precious memory space for BMS. And it also reduces the network and computation loads. However, it leads to a side effect that the trend of signal distortion is enhanced. The optimal recording frequency in practice should be as low as possible on the condition that little signal distortion happens. This paper presents a novel method which uses a multi-frequency recording technology that cooperates two approaches according to the signal dynamics. A flexible recording frequency method is applied for stationary signals which only records signals when their values are changed. While for dynamic signals, the most dynamic period is found using discrete wavelet transformation (DWT) and further analyzed by fast Fourier transformation (FFT). By comparing two recording signal indicators for four different recording frequencies, we conclude that recording at 1 Hz is not qualified for the cell voltage and current during the dynamic period in our system due to the high dynamic performance of the vehicle. In the demonstrated vehicle, only by increasing the recording frequency to at least 2 Hz, can the accuracy of the recorded cell voltage achieve the level the same as the measurement accuracy in engineering. And we also verify that when the recording frequency is reduced to the optimal frequency compared to the high frequency recorded original signals, the accuracy of the SOC estimation is not influenced.

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.

Proton exchange membrane fuel cells have shown great promise for powering trams. Hydrogen refueling stations and a fuel-cell system incur initial vehicle costs that are higher than a pantograph/catenary tram or contact-rail tram. In this paper, a life-cycle cost analysis is conducted for five trams: a pantograph/catenary tram, a contact-rail tram, and three fuel-cell hybrid trams. Characteristics of fuel-cell hybrid trams are compared with contemporary transit systems. A simplified life-cycle cost model, including costs for the initial infrastructure and powertrains, daily operation and power plant replacement, is proposed and calculated with parameters. A sensitivity analysis is also performed. Results show that the life-cycle costs of trams are almost proportional to the rail-line length. The initial costs of a fuel-cell hybrid tram are less than a pantograph/catenary tram or contact-rail tram. The life-cycle costs of fuel-cell hybrid trams are highly dependent on combination factors of hydrogen price, fuel-cell price and battery price. Charging facilities for fuel-cell hybrid trams are favorable when hydrogen price is in a high level. Greenhouse gas emissions of trams are almost equivalent.

A control-oriented model about PEM fuel cell system with anodic and cathodic exhaust gas recirculation is introduced in this paper. It contains anode and cathode system model, fuel cell stack model which contains water transport model, oxygen transport model, nitrogen transport model, voltage model and stack cooling system model. Only the water transport model is introduced here. Then the model is verified by experiment. Results show a good agreement between the simulated and measured cell voltages, cathode inlet molar water concentrations.

With advantages like high efficiency, low pollution, and convenience of structure layout, the electric vehicles have been developing to become the main research direction of the automobile industry. Compared with the traditional centralized drive mode, the distributed electric drive can improve the power transmission efficiency and the fault tolerance. As the distributed electric drive technology developing in the field of multi-axle vehicles, research for mature dynamic coordinated control strategy has been an important task of the researchers in the automobile industry. This paper was aimed at the dynamic coordinated control strategy of multi-axle vehicles. Due to the independent driving characteristics of distributed drive multi-axle vehicles, a lateral dynamic control method using electronic differential moment power steering was proposed and verified, which can improve driving reliability, steering performance and vehicle mobility. A control model of six-axle-distributed-electric-drive vehicle was set up. With the MATLAB/Simulink software, the C code of the control model was generated and eventually burnt into the vehicle control unit (VCU). Then the hardware-in-the-loop experiment was successfully implemented on the motor bench, verifying the feasibility of the control algorithm.

This paper presents a novel energy management strategy for a dual-engine system adopted in a series hybrid heavy-duty vehicle. The studied vehicle is powered by Li-ion batteries and two auxiliary power units (APUs). The model of the studied powertrain is established. Simulations under two Chinese-World Transient Vehicle Cycles (C-WTVCs)are conducted using the Charge Depleting and Charge Sustaining (CDCS)strategy. A power distribution strategy between two diesel engines is proposed to improve the system efficiency. The proposed power distribution strategy is compared with other strategies and can decrease the energy consumption by up to 8.7%. The dual-engine system is also compared with a conventional series hybrid heavy-duty vehicle with single engine. Simulation results show that different powertrains have similar energy efficiencies while the dual-engine system has additional merits such as good fault-tolerance ability.

Fuel economy is an important index for fuel cell hybrid powertrain system. Because fuel economy can be affected by control strategies, test protocols and system design, traditional economy analysis method should calculate all fuel economy results under different strategies and protocols. In this paper, a three-step evaluation method has been proposed for fuel cell hybrid powertrain system fuel economy analysis. For a fuel cell hybrid system system, effeciency curve is used for fuel cell system economy analysis, average power demand variation is used for fuel cell hybrid system economy analysis, output power histogram is used for energy management strategy analysis. It has been validated that this method can be used to guide the system design and fuel economy evaluation.

There is a lack of appropriate models to delineate the toxicity of rare earth elements (REEs) while taking into account the factors that affect bioavailability. Here, standardized wheat (Triticum aestivum L.) root elongation tests were conducted to examine the impact of exposure conditions (i.e., varying Ca, Mg, Na, K and pH levels) on Y and Ce toxicity. Cation competition and electrostatic theory were examined for their applicability in explaining the observed variations in toxicity. Only Ca2+ and Mg2+ significantly alleviated the toxicity of Y3+ and Ce3+, while Na+, K+ and H+ showed no significant effects. Based on the cation competition, the derived binding constants for the hypothetical biotic ligands of wheat logKCaBL, logKMgBL, logKYBL, and logKCeBL were 3.87, 3.59, 6.70, and 6.48, respectively. The biotic ligand model (BLM) succeeded in predicting toxicities of Y and Ce, with more than 93% of the variance in toxicity explained. Given the BLM requires large data sets for deriving model parameters, attempts were further made to explore a simpler electrostatic based model to quantify REEs toxicity. The results demonstrated that the predictive capacity of the electrostatic approach, which considers ion activities at the plasma membrane surface, was comparable to that of BLM with at least 87% of the variations in toxicity explained. This suggested that the electrostatic theory can serve as a surrogate to BLM in modeling Y and Ce toxicities. Therefore, we recommend the BLM and electrostatic-based model as effective approaches to incorporate bioavailability in quantifying REEs toxicity in the presence of various levels of other major cations.

In order to improve the output power of fuel cell in automobile under dynamic load and prolong its working life, it is necessary to understand the spatial inconsistency and sensitivity of its internal state. A simplified two-dimensional model of the proton exchange membrane fuel cell is established. The average and deviation values of internal states is calculated. The sensitivity of the internal states to the operating conditions of the fuel cell is analyzed. Results show that the sensitivity of different variables to operating conditions is different. The water vapor pressure is more sensitive. The temperature and voltage are the key factors of sensitivity analysis.

There is a lack of appropriate models to delineate the toxicity of rare earth elements (REEs) while taking into account the factors that affect bioavailability. Here, standardized wheat (Triticum aestivum L.) root elongation tests were conducted to examine the impact of exposure conditions (i.e., varying Ca, Mg, Na, K and pH levels) on Y and Ce toxicity. Cation competition and electrostatic theory were examined for their applicability in explaining the observed variations in toxicity. Only Ca

The continuous chemical degradation of the polymer membrane in polymer electrolyte fuel cells causes membrane pinhole formation, therefore substantial increase in the gas cross-over flux. In this paper, a numerical method to simulate the pinhole formation process during chemical degradation is proposed. The method assumes that a membrane pinhole is formed by connected local micro-pores, which are generated owing to the mass loss during chemical membrane degradation. In addition, pinhole formation is combined with reduction of the membrane thickness to account for the membrane structure changes. A dynamic chemical degradation model that incorporates the effects of membrane structure changes is validated against the experimental results of the accelerated stress test. Results confirm the proposed method increases the accuracy of the chemical degradation model in predicting the macroscopic properties, including cumulative mass loss, hydrogen cross-over and open circuit voltage. Formation of pinhole starts from the anode, where degradation is more severe, and propagates to the cathode. The model also systemically studies the effects of temperature, pressure, and relative humidity on chemical degradation. The degradation rate increases with elevated temperatures and pressures. The degradation is shown to be more severe at moderate relative humidity, and the comparison with experimental findings are discussed.

In order to enhance the power and bring additional energy-saving possibilities of heavy-duty vehicles, a novel dual-engine system is utilized in a series hybrid electric vehicle. However, the minimum fuel consumption of this configuration is still unclear, and the effective online energy management strategy for this system is absent. The studied vehicle adopts the dual-engine configuration, which is powered by Li-ion batteries and two auxiliary power units. This paper presents a two-step framework to address the energy management problem. A map-based strategy is adopted to distribute power between engines. The dynamic programming (DP) algorithm is incorporated to distribute power between engines and batteries and find the minimum fuel consumption. Simulation results show that the DP algorithm can save 7.3% fuel compared to the charge depleting and charge sustaining strategy. The dual-engine system achieves a 1.9% lower fuel consumption compared with the conventional hybrid system with one engine. The operation points of engines and the power profiles of batteries derived from the DP are analyzed, and a rule-based strategy is designed correspondingly. The proposed rule-based algorithm can reduce 2.2%–6.0% fuel consumption and is not sensitive to the variations of battery size, parameters of the rule-based strategy, and driving cycles.

The nonlinear, accelerated decline of fuel cells is a major cause of diminished service life, which is difficult to be detected in early warning. Through in situ electrochemical diagnosis, we found that the accelerated decline of fuel cell could not be directly predicted by the crossover current or the electrochemically active surface area. Surface analysis of catalyst layer showed that the inverse flow of the cathode and anode may lead to dry-wet cyclic stress and corrosion of the catalyst layer in the cathode inlet area (anode outlet area). This leads to cracking in the catalyst layer and corrosion of the carbon support. What’s more, the uncorroded electrolyte will then fill in the original microporous structure, resulting in a decrease in the porosity of the catalyst layer and a corresponding accelerated decline its mass-transfer performance. According to a semi-quantitative model, a 50% corrosion of the catalyst layer leads to a decrease of up to 80% in the equivalent diffusion coefficient, the key mechanism inducing the local performance decline, which leads to accelerated decline of the overall fuel cell performance. This is particularly important for vehicle fuel cells where the local deterioration caused by the uneven distribution of hydrothermal states induces accelerated decline.

Low temperature charging is a major challenge for lithium-ion batteries, since it could lead to dramatic performance degradation and potential safety issues. A pre-heating process is usually applied to overcome above-mentioned challenges. Pulsed operation is adopted as one of established internal pre-heating methods with good temperature uniformity. Herein we employed and investigated bidirectional pulsed current through experimental methods to obtain the main data of the thermal action for comprehensively analyzing heat generation characteristics and thermoelectric coupling model based on second-order RC circuit to verify the basic principle. Battery durability research was then conducted via a continuous heating test method which enables rapid testing of capacity degradation. The results indicated that proposed pulsed heating could not significantly damage the life span from the perspective of long-term applications: the battery has only 1% capacity decay after 170 h continuous heating with a heating rate of 11 °C/min. Parameters, which are beneficial for heating rate, are further found to be detrimental for degradation and vice versa. Nevertheless, based on the outcome of this study, the pulse waveform with a shorter period and a higher amplitude are suggested to give an optimal combination of higher heating rate and lower degradation. Such a pulsed heating method has several potential application scenarios, ranging from electric vehicles and even stationary storage systems.

In this study, an agricultural residue-derived biochar was fabricated by pyrolyzing coffee shells using (NH4)3PO4 pretreatment. The influence of pyrolysis temperature on the structure and properties of biochars was investigated. The elemental analysis, spectroscopic and textural studies showed that the biochars were endued sufficient N and P co-doping and large specific surface area by (NH4)3PO4-pretreatment. The appraisement for remedying aqueous Cr(VI) contaminants demonstrated that the N/P co-doped biochars offered high efficiencies above 95% for aqueous Cr(VI) removal. The mechanism investigation displayed that the adsorption and reduction of Cr(VI) were boosted by the synergistic effect between the hierarchical pore structure and the groups related to oxygen, nitrogen and phosphorus. Moreover, the biochar can be readily regenerated by HCl solution soaking for reuses several times. This work should permit for providing a convenient utilization of coffee shell agricultural residues, and the coffee shell-derived biochars supplied potential for remedying Cr(VI) in effluents.

Durability is one of the key issues in commercialization of proton exchange membrane fuel cell (PEMFC). The main purpose of this study is to investigate the degradation mechanism of Membrane Electrode Assembly (MEA) based on PTFE/Nafion composite membrane in PEMFC through the MEA/Stack Durability Protocol developed by the Fuel Cell Technical Team (FCTT) of the Freedom CAR and Fuel Partnership. The accelerated life test lasted for 300 h, with voltage decay rate of the MEA about 0.48 mV/h at operating current density 100 mA/cm2 being achieved. After the acceleration experiment, degradation mechanisms for the MEA based on PTFE/Nafion composite membrane were analyzed in detail by hydrogen-thermal experiment, SEM, TEM, EDS and Ion Chromatographic test. The experimental results show that pinhole formed at outlet position of the composite membrane leads to hydrogen crossover current density exceeding 21 mA/cm2 at 210 h, with F− and SO42− concentrations sharply increased around 200 h in discharge water of fuel cell from IC results, therefore, membrane failure is the major factor in the failure of MEA. Moreover, the micro-structural damage in the MEA and Pt particles growing up along flow channel even appearing at membrane could be observed from SEM, TEM and EDS results, which play important role in the deterioration of performance and stability for PEMFC.

Fuel cell hybrid electric vehicles are attracting increasing attention and research. However, the durability of fuel cell systems (FCS) is the main bottleneck in commercial application. A plug-in fuel cell city bus was developed by our group, and it completed several months of demonstration operation. A two-stage flowchart was proposed to clarify the FCS degradation analysis. The average cell voltage decline rate is approximately 346 μV/h at a current density of 120 A, under which the initial voltage is about 0.7 V. The estimated lifetime in the third stage reaches the design target. The final electrochemically active surface areas are approximately 80% of the initial value. A detailed degradation analysis of fuel cell voltage uniformity is presented, and a five-region degradation otherness analysis is proposed for performance uniformity analysis. The difference of equivalent resistance has been verified to be the main factor in degradation otherness of the regions and in system performance degradation.

Accurate estimation of the capacity of a battery pack is essential for the battery management system (BMS) in electric vehicles. The SOCs and capacities of individual cells are the prerequisites for accurately estimating the capacity of a battery pack. This paper proposes quantitative analysis on how the estimation errors of individual cells’ SOCs and capacities influence the estimation error of the battery pack capacity using an approach named Capacity–Quantity diagram (C–Q diagram). The analysis concludes that the estimation error of cell SOC has more influence on the estimation error of pack capacity than the estimation error of cell capacity does. The theoretical analysis is further validated by an experiment using six NCM batteries connected in series with different initial SOC variations. The results help to guide the determination of specifications, e.g., the estimation error of the SOC and that of the capacity, during the design process of a BMS.

A one-dimensional model accounting for chief water transport phenomena in proton exchange membrane (PEM) fuel cell is developed. The water transfer process in catalyst layers (membrane water absorption/desorption) is explicitly taken into account and the mathematical descriptions of the Schroeder's paradox are presented in this model. In addition, to solve two-phase problems in gas diffusion layers (GDLs) without using complex numerical approach, the assumption of an infinite phase change rate is applied and the analytical solutions to the two-phase model equations are derived. Based on the model and the analytical solutions, an identification procedure using the iterative approach is proposed to (1) determine the net water flux through the membrane, (2) obtain exact water profiles in all components of PEM fuel cell and (3) predict the dehydration and flooding. The AC impedance technique is used to analyze the cell performance and the predicting capability of the model-based approach is validated. The measurements and predictions both reveal the effect of electro-osmotic drag on drying the anode at high current and the trade-off between membrane dehydration and water flooding in the cell.

The powertrain plays an essential role in improving the tractive performance and the fuel consumption of fuel cell hybrid vehicles. This paper presents a comparative study of two different powertrains for fuel cell hybrid buses. The significant difference between the two powertrains lies in the types and arrangements of the electrical motor. One powertrain employs an induction motor to drive the vehicle, while the other powertrain adopts two permanent magnetic synchronous motors for near-wheel propulsion. Besides, the tiny difference between the proposed powertrain is the supply path of the fuel cell accessories, which can have an effect on the powertrain efficiency. The component parameters and energy management strategies for the two powertrain are determined. The fuel cell hybrid buses equipped with the two powertrains are developed, and some road tests are achieved, according to the chosen procedures or driving cycles. The paper focuses on the tractive performance and energy analysis of the powertrains based on the testing results. Finally, the paper summarizes the relative merits of the proposed powertrains.

This paper presents the results of a research project aimed at developing and evaluating the viability of fuel cell vehicles for urban public transit applications and investigating ways to commercialize them. Considering a low-floor bus design and high efficiency of powertrain, one of the salient characteristics of the proposed fuel cell/battery hybrid bus is the E-drive axle, which integrates two near-wheel permanent magnet synchronous motors (PMSMs) in the rear axle. As an important part of the vehicle's powertrain, the E-drive axle was employed to drive the vehicle, capture the breaking energy and match the required speeds of the differential. The configuration and parameters of the powertrain of the hybrid fuel cell/battery bus are given in detail. To extend the life of the fuel cell stacks, the change in the output power of fuel cell stacks is controlled to be gradual via a DC–DC converter depending on the energy management strategy, which was described in this paper. An energy analysis based on a chosen driving cycle has been conducted to study the efficiency of the proposed powertrain, which shows that the hydrogen consumption of the bus is 13.29 km/kg. Also, the road test results indicated the tractive capabilities and maneuverability of the bus can reach the design specifications.

The electrochemical impedance spectroscopy (EIS) technique is now widely used in the study of the hydrogen polymer electrolyte membrane fuel cell (PEMFC), especially the diagnosis of flooding and drying. Though the working conditions of fuel cell vehicles is fairly rough with large electromagnetic interference and ever-changing environment, lots of efforts have been made to prompt the online EIS analysis of PEMFC stack in vehicles, such as using a DC/DC converter based on the ripple currents or active voltage control and so on. Considering the practical topologies of fuel cell powertrain systems, their researches inspire us to put forward a simpler approach in terms of applicability and controllability. For this reason, a topology of two parallel boost DC/DC converters for online AC impedance estimation of PEMFC stack is proposed. This topology is modeled using Matlab/Simulink. To better understand the electrical characteristic of PEMFC, equivalent circuits are utilized to model the PEMFC based on the electrochemical reactions and mass transport properties in the fuel cell. Fluctuation signals produced by a DC/DC converter are injected into the stack. The other DC/DC converter is used to adjust the output characteristic of the stack to the output voltage and current requirements of the external power devices and load. In this way, the fluctuation signal generation and power conversion are decoupled, which is more suitable for different applications of PEMFC stack. To effectively control these converters, closed-loop PI controllers are adopted and coefficients are regulated according to the frequency of disturbance signals. Based on this model, simulation results show that fluctuation signals are well generated and injected into the stack with low total harmonic distortion (THD). After analysis of the output voltage and current of the stack using FFT technique, AC impedance calculated is in consistent with the impedance characteristic of the equivalent circuits with high accuracy.

This paper presents a thermal analysis of a semi-active battery/supercapacitor (SC) hybrid energy storage system (HESS), which is used in electric vehicles (EVs), at subzero temperatures. In subzero temperature environments, EVs suffer a dramatic driving range loss due to the energy and power capability reduction of LiFePO4 batteries, as well as severe battery degradation due to Li plating. This will increase the system operation cost because the battery pack needs to be changed frequently. Based on a novel degradation model of LiFePO4 batteries, which is validated over a wide temperature range, a near-optimal energy management strategy of the HESS for on-line use is proposed using the dynamic programming (DP) approach, which minimizes the operation cost (the electricity and the battery fade costs) over a typical China Bus Drive Cycle (CBDC). The convective heating method is integrated into the DP process. Finally, the required heating of the HESS at subzero temperatures over multi-CBDC is analyzed by evaluating the system operation cost. Simulation results show that the heating process becomes increasingly necessary with increased driving range, battery price, and heating efficiency, as well as decreasing environment temperature.

A typical topology of a proton electrolyte membrane (PEM) fuel cell electric vehicle contains at least two power sources, a fuel cell system (FCS) and a lithium battery package. The FCS provides stationary power, and the battery delivers dynamic power. In this paper, we report on the multi-objective optimization problem of powertrain parameters for a pre-defined driving cycle regarding fuel economy and system durability. We introduce the dynamic model for the FCEV. We take into consideration equations not only for fuel economy but also for system durability. In addition, we define a multi-objective optimization problem, and find a quasi-optimal solution using a two-loop framework. In the inside loop, for each group of powertrain parameters, a global optimal energy management strategy based on dynamic programming (DP) is exploited. We optimize coefficients for the DP algorithm to reduce calculating time as well as to maintain accuracy. For the outside loop, we compare the results of all the groups with each other, and choose the Pareto optimal solution based on a compromise of fuel economy and system durability. Simulation results show that for a “China city bus typical cycle,” a battery capacity of 150 Ah and an FCS maximal net output power of 40 kW are optimal for the fuel economy and system durability of a fuel cell city bus.

Poor water management usually leads to various degrees of flooding and exacerbates oxygen starvation, both of which affect the performance and durability of a proton exchange membrane fuel cell (PEMFC). This paper proposes a model-based approach to estimating the liquid saturation and current density difference simultaneously. The current density difference is a parameter that indicates the oxygen starvation level. For estimation purposes, a fuel cell cathode model with separate inlet and outlet subsystems is developed to incorporate the effect of harmful phenomena such as flooding and oxygen starvation on the system dynamics and cell voltage. The cathode gas diffusion layer (GDL) flooding and oxygen starvation diagnoses are formulated as state estimation problems. The proposed approach is validated through an offline simulation using experimental data. The offline prediction suggests the effect of the anode purge and air steam conditions on the internal states of the PEMFC, which is helpful for system optimization and control design. The estimation problems are further decoupled, and a simplified algorithm is designed for onboard applications. Finally, the modified fuel cell model and optimized estimation algorithm are applied to an online test system as a demonstration.

This paper proposes an energy flow model and an optimal energy management strategy based on mean values for maximizing driving mileage of a fuel cell bus (FCB), which is powered by a polymer electrolyte membrane (PEM) fuel cell system and a lithium battery. Firstly, an energy flow model describing the relations between vehicle performance and power flow parameters is quantitatively established. An optimization problem for maximizing driving mileage on a predetermined route is defined, and an analytical solution with clear physical meanings is derived. Next, a practical real-time supervisory Energy Management strategy basing on Mean Values (EMMV) is proposed. The strategy, which doesn't require a priori knowledge of the driving trip, is then compared with several well-known strategies, e.g. charge depleting and charge-sustaining (CDCS), Blended, dynamic programming (DP), and Pontryagin's Minimum Principle (PMP). Simulation results show that, the proposed strategy achieves a near-optimal effect, and converges after one driving cycle on a predetermined bus route. Finally, on-road testing is carried out. The proposed strategy achieves an average endurance mileage on a real bus route of 162 km with a usable battery state of charge (SOC) of 90% and 20 kg hydrogen gas for a fully loaded fuel cell city bus.

Energy conservation is a very important task for the automotive industry. The use of hybrid electric vehicles can improve energy efficiency, thus reducing fuel consumption and carbon emissions. In this research, the performance characteristics of a novel coaxial power-split hybrid powertrain for a transit bus are presented. The power sources are a combination of a compressed natural gas (CNG) engine and supercapacitors. A mathematical model for the coaxial power-split hybrid powertrain is established. Subsequently, an analysis program is developed based on Matlab and Advisor. The parameters are specified using experimental data. Afterwards, a rule-based control strategy is designed and optimized from the viewpoint of energy efficiency. Later, the system performance is evaluated using the Chinese Transit Bus City Driving Cycle and compared to a conventional powertrain. The results indicate that the proposed coaxial power-split hybrid powertrain can fulfill the requirements of the transit bus and enhance the energy efficiency dramatically. Moreover, the average energy efficiency of the supercapacitors was found to be above 97% over the entire driving cycle. Using supercapacitors as energy storage devices for the coaxial power-split hybrid powertrain can effectively recover the kinetic energy during regenerative braking and is a good solution for transit buses that require frequent acceleration and deceleration.

In Polymer Electrolyte Membrane Fuel Cells (PEMFCs) with Dead-Ended Anode (DEA) configuration, precise control of hydrogen pressure in anode is beneficial for better performance and durability of fuel cell systems. In most studies, mechanical pressure regulator is implemented to modulate the hydrogen pressure. But when load changes or purge operation activates, hydrogen pressure downstream the regulator varies with hydrogen flow fluctuation. In this study, a hydrogen injection system is developed utilizing gaseous fuel injectors. Based on a fuel cell simulation test bench, the performance of the hydrogen injection system is evaluated. A physics-based nonlinear model of the simulation test bench is presented in this paper. Experimental results validate the model. The model is further linearized and integrated in a Robust Predictive Controller (RPC), a Model-Based Controller (MBC), and an H∞ controller, respectively, in order to compare the control effects on the hydrogen pressure, especially the mitigation of the pressure swing during the purge operation. A comparative study is carried out under different scenarios, i.e. target pressure step response, hydrogen consumption mass flow step response, and periodical pulse response during the purge operation. According to the results, MBC is chosen for injection control, since the system demonstrates preferable performance in comparison with other controllers. Finally, pressure fluctuation data of both simulation test bench with hydrogen injection and conventional mechanical pressure regulator is compared to elucidate the effectiveness.

Temperature changes in PEM fuel cell stacks affect gas transfer, water balance, and electrochemical reaction activities. Improper temperature regulation could impact the durability of the stack, which is of the highest importance for a city bus. Hence, thermal management is an important issue for PEM fuel cell, especially for city bus applications. In this study, a model-based control strategy aimed at keeping the temperature in a small range near target value was applied to a cooling system. Firstly, the cooling system of the PEM fuel cell system was proposed and the cause of temperature fluctuation was analyzed. Then, a model of the cooling system, which consisted of a stack, a water tank, and a radiator coupled to a fan, was built on the Simulink platform. A model-based controller consisting of nonlinear feedforward and LQR state feedback was added to the model. The simulation results showed that the controlled system performed satisfactorily. Also, when applied on a real system, the controller worked out well. Data collected from the city bus show that the temperature of the stack is kept in a range within ±0.5 °C.

Internal short circuit (ISCr) detection of a battery is critical for preventing thermal runaway and enhancing electrical vehicle safety. In this paper, the electrical characteristics of the ISCr of a large format lithium ion battery are analyzed using the equivalent circuit model (ECM). An ISCr detection method is developed based on battery consistency within the battery pack. The ISCr detection method employs the recursive least square (RLS) algorithm based on the mean-difference model (MDM), which is derived from the ECMs consisting of the mean and difference value of cells' voltage and resistance. The algorithm first estimates the basic parameters of the MDM. Then the algorithm calculates the characteristic parameters, such as the differential of the voltage and the fluctuation function of the internal resistance, derived from the basic parameters of the MDM. These characteristic parameters obviously vary once ISCr occurs, thereby helping the battery management system to realize ISCr detection. The effectiveness of the ISCr detection method is validated through a series of experiments.

The rotor position is a key state in the closed-loop control system of the permanent magnet synchronous motor (PMSM). Its measurement accuracy has a significant effect on steady accuracy, dynamic response, and torque ripple. The magnetoresistance (MR) sensor is widely used in the rotor position detection due to its distinct advantages, such as simple structure, high sensitivity, and strong robustness. In this paper, a solution using the giant magnetoresistance (GMR) sensor in TLE5309D chip for angle measurement is introduced, and its feasibility is verified by finite element analysis (FEA) simulation and bench test. In the simulation, two schemes different in the sensor location and the number of permanent magnet poles, are evaluated according to the higher harmonic content and field direction stability near the sensor. The experiment from 1 rpm to 1000 rpm is implemented, and the measurement results after calibration based on discrete Fourier series (DFS) show that the GMR sensor has a good performance in the test.

Sub-zero startup ability remains a key barrier for commercial application of polymer electrolyte fuel cells (PEMFC), especially for automotive applications. In order to improve the startup ability and durability of fuel cells, understanding of the characteristics and mechanisms of cold start is essential, and here modeling of fuel cell cold start plays an important role. In this study, a one-dimensional model is developed to simulate the fuel cell cold start. The model includes mass transport and phase change, heat transfer and electrochemical reaction. Key features such as membrane water and local current distributions are analyzed. Based on the one-dimensional model and simulation results, a spatial reduced simplified model is developed that distinguished only n states across the cell. The simplified model inherits the key features of the one-dimensional model, while the computational cost is significantly reduced to 10% (from 216 s to 20.88 s). The one-dimensional model and simplified model are both validated by the cold start experiment and the voltage error and temperature error are within 15% and 1.2 K respectively. Thus, the proposed simplified model could be used in dynamic simulation and in further multi-scale modeling study to build a stack model.

The paste prepared from hemihydrate phosphogypsum (HPG) and tailing (HTP) differs greatly from the cement tailings paste (CTP). The rheological behavior of HTP including the visual flow ability and rheology was uncovered in the present study. The suitable mass concentration of HTP was determined by fluidity and bleeding tests firstly. Then, the rheological parameters and thixotropy were analyzed based on rheological tests. Compared with CTP, HTP has higher ultimate yield stress, smaller yield stress and plastic viscosity, and shorter thixotropic time. Finally, the rheological properties with different resting time and shearing time were studied. The results showed that the rheological stability deteriorated with time, especially in the resting state. The special rheological behavior of HTP may be attributed to the stable mosaic structure, which was related to the particles size and shape. In addition, the HPG hydration will enhance the structure, resulting in the rheological stability of HTP weakening gradually. This work may pave ways to the understanding of the HTP mixing and transport process.

Battery electric vehicles with a range of more than 500 km are expected to become increasingly competitive in the future. The energy density of the currently available lithium batteries should be significantly increased to support the operation of such vehicles, and high-power charging is required to reduce the charging time. However, high-power charging may negatively affect the durability and safety of lithium batteries because of increased heat generation, capacity fading, and lithium plating, which can induce the risk of battery thermal runaway. Currently, there are no established boundary conditions for high-power charging or methods for evaluating its risks, especially in case of high-capacity lithium batteries. This study proposes a test procedure for examining the reaction characteristics of the capacity fading and thermal tolerance of lithium batteries that are subjected to high-power charging. Further, the migration characteristics of the temperature threshold of battery thermal runaway are investigated using the proposed procedure. The test results demonstrate that high-power charging significantly impacts the durability and thermal safety of the high-capacity lithium batteries. In particular, the capacity fading rate can reach up to 30% only after 100 charge cycles depending on the battery type. Furthermore, the thermal tolerance can decrease up to 40% by considering the change in the self-heating temperature as an indicator. Based on the study results, it can be concluded that the thermal management systems should be carefully designed to satisfy the high-power charging requirements. Otherwise, the high power charging only can be performed with limited range for battery electric cars with long all electric range.

Rare earth elements (REEs) are typically present as mixtures in the environment, but a quantitative understanding of mixture toxicity and interactions of REEs is still lacking. Here, we examined the toxicity to wheat (Triticum aestivum L.) of Y, La, and Ce when applied individually and in combination. Both concentration addition (CA) and independent action (IA) reference models were used for mixture toxicity analysis because the toxicity mechanisms of REEs remain obscure. Upon single exposure, the EC50s of Y, La, and Ce, expressed as dissolved concentrations, were 1.73 ± 0.24 μM, 2.59 ± 0.23 μM, and 1.50 ± 0.22 μM, respectively. The toxicity measured with relative root elongation followed La Y ≈ Ce, irrespective of the dose descriptors. The use of CA and IA provided similar estimates of REE mixture interactions and toxicity. When expressed as dissolved metal concentrations, nearly additive effects were observed in Y-La and La-Ce mixtures, while antagonistic interactions were seen in Y-Ce mixtures. When expressed as free metal activities, antagonistic interactions were found for all three binary mixtures. This can be explained by a competitive effect of REEs ions for binding to the active sites of plant roots. The application of a more elaborate MIXTOX model in conjunction with the free ion activities, which incorporates the non-additive interactions and bioavailability-modifying factors, well predicted the mixture toxicity (with92% of toxicity variations explained). Our results highlighted the importance of considering mixture interactions and subsequent bioavailability in assessing the joint toxicity of REEs.

Water management is critical for the operation of a polymer electrolyte membrane fuel cell (PEMFC). For the purposes of high power and long working-lifetime of PEMFCs, external humidifiers are always utilized as a necessary part of balance of plants to keep the imported air and fuel wet. However, they have several disadvantages, and it is beneficial to remove them so as to reduce system volume and to enhance the cold-starting capability. In this paper, a self-humidified PEMFC of an active area 250 cm2 and cell number 320 is proposed and investigated. The imported dry air on the cathode side is mixed with moisty exhaust gas by using a recirculation valve, and the dry hydrogen on the anode side is humidified by back-diffusion water through the membrane. A nonlinear model is set up based on mass transport and energy conservation equations to capture dynamics of gases in the supply and exhaust manifolds, the gas diffusion layers (GDLs), and the membrane. An analysis is conducted to investigate the influences of parameters on dynamic and stable performances. Simulation results show that system performances can be greatly affected by parameters such as air stoichiometry, current density, exhaust gas recirculation (EGR) ratio, and membrane thickness. By accurately controlling the EGR ratio and carefully selecting design and operation parameters, it is probably for a PEMFC without an external humidifier to have similar system efficiency compared to a traditional system.

Coulombic efficiency (CE) is an important parameter for battery cells. Unfortunately, precise measurement of CE is extremely difficult, so CE is seldom focused during cell performance study. Nevertheless, correlation between stage of charge (SOC) and CE has significant impact on battery pack performance, while the influences of different correlations between SOC and CE on battery packs have never been explored as far as we know. We present a novel method which implements two series-connected cells that can determine the correlation between SOC and CE. The experimental result shows that CE is almost invariant with SOC changes for the experimental commercial LiFePO 4 /C cells. This paper further investigates series-connected cells with three typical correlations between SOC and CE in simulations. The simulation results indicate that cells with negative correlations between CE and SOC are preferred for series-connected battery packs, as they tend to diminish SOC difference and increase the pack capacity which can be considered as a self-balancing mechanism.

In order to estimate the remaining driving range (RDR) in electric vehicles, the remaining discharge energy (ERDE) of the applied battery system needs to be precisely predicted. Strongly affected by the load profiles, the available ERDE varies largely in real-world applications and requires specific determination. However, the commonly-used direct calculation (DC) method might result in certain energy prediction errors by relating the ERDE directly to the current state of charge (SOC). To enhance the ERDE accuracy, this paper presents a battery energy prediction (EP) method based on the predictive control theory, in which a coupled prediction of future battery state variation, battery model parameter change, and voltage response, is implemented on the ERDE prediction horizon, and the ERDE is subsequently accumulated and real-timely optimized. Three EP approaches with different model parameter updating routes are introduced, and the predictive-adaptive energy prediction (PAEP) method combining the real-time parameter identification and the future parameter prediction offers the best potential. Based on a large-format lithium-ion battery, the performance of different ERDE calculation methods is compared under various dynamic profiles. Results imply that the EP methods provide much better accuracy than the traditional DC method, and the PAEP could reduce the ERDE error by more than 90% and guarantee the relative energy prediction error under 2%, proving as a proper choice in online ERDE prediction. The correlation of SOC estimation and ERDE calculation is then discussed to illustrate the importance of an accurate ERDE method in real-world applications.

Charging procedures at low temperatures severely shorten the cycle life of lithium ion batteries due to lithium deposition on the negative electrode. In this paper, cycle life tests are conducted to reveal the influence of the charging current rate and the cut-off voltage limit on the aging mechanisms of a large format LiFePO 4 battery at a low temperature (−10 °C). The capacity degradation rates accelerate rapidly after the charging current reaches 0.25 C or the cut-off voltage reaches 3.55 V. Therefore the scheduled current and voltage during low-temperature charging should be reconsidered to avoid capacity degradation. Lithium deposition contributes to low-temperature aging mechanisms, as something needle-like which might be deposited lithium is observed on the surface of the negative electrode after disassembling the aged battery cell. To confirm our explanation, incremental capacity analysis (ICA) is performed to identify the characteristics of the lithium deposition induced battery aging mechanisms. Furthermore, the aging mechanism is quantified using a mechanistic model, whose parameters are estimated with the particle swarm optimization algorithm (PSO). The loss of reversible lithium originating from secondary SEI formation and dead lithium is confirmed as the cause of the aging.

This paper presents a robust gain-scheduled H∞ controller to improve lateral stability and handling of four-wheel-independent-drive electric vehicles possessing active front steering system with considerations of state delay. The time delay for the state is assumed as uncertain time-invariant but has a known constant bound. By considering the tyre cornering stiffness represented by the norm-bounded uncertainty and the time-varying longitudinal velocity described by a polytope with finite vertices, and the vehicle lateral dynamics model is converted into the uncertain vehicle linear parameter-varying LPV state-delayed system. The resulting delay-dependent robust gain-scheduling state feedback H∞ controller is finally designed utilizing the constructed Lyapunov-Krakovskii functional, and solved via a set of delay-dependent linear matrix inequalities LMIs. Simulations for various driving scenarios are implemented using MATLAB/SIMULINK-CARSIM. The simulation results show the effectiveness of the proposed controller.

Drive wheel systems combined with the in-wheel permanent magnet synchronous motor (I-PMSM) and the tire are highly electromechanical-coupled. However, the deformation dynamics of this system, which may influence the system performance, is neglected in most existing literatures. For this reason, a deformable tire and a detailed I-PMSM are modeled using Matlab/Simulink. Furthermore, the influence of tire/road contact interface is accurately described by the non-linear relaxation length-based model and magic formula pragmatic model. The drive wheel model used in this paper is closer to that of a real tire in contrast to the rigid tire model which is widely used. Based on the near-precise model mentioned above, the sensitivity of the dynamic tire and I-PMSM parameters to the relative error of slip ratio estimation is analyzed. Additionally, the torsional and longitudinal vibrations of the drive wheel are presented both in time and frequency domains when a quarter vehicle is started under conditions of a specific torque curve, which includes an abrupt torque change from 30 N · m to 200 N · m. The parameters sensitivity on drive wheel vibrations is also studied, and the parameters include the mass distribution ratio of tire, the tire torsional stiffness, the tire damping coefficient, and the hysteresis band of the PMSM current control algorithm. Finally, different target torque curves are compared in the simulation, which shows that the estimation error of the slip ratio gets violent, and the longitudinal force includes more fluctuation components with the increasing change rate of the torque. This paper analyzes the influence of the drive wheel deformation on the vehicle dynamic control, and provides useful information regarding the electric vehicle traction control.

This paper investigates the overcharge-induced capacity fading behavior of large format lithium-ion batteries with Li y Ni 1/3 Co 1/3 Mn 1/3 O 2 + Li y Mn 2 O 4 composite cathode. The capacity degradation mechanism is studied using a prognostic/mechanistic model and incremental capacity analysis (ICA). The overcharge process can be divided into four stages. Loss of active material (LAM) in both the cathode and the anode and loss of lithium inventory (LLI) in different overcharge stages are quantified using the prognostic/mechanistic model. In Stage I, the battery shows no obvious capacity degradation until it is overcharged to 120% state of charge (SOC). In Stage II, LLI occurs as a result of lithium deposition, with LAM in the Li y Mn 2 O 4 of the composite cathode. Internal resistance increases in Stage II indicating the thickening of the SEI film. In Stage III, LAM in both the cathode and the anode happen as the battery is overcharged to over 140% SOC. The battery starts to swell in this stage, as a result of the electrolyte oxidation. In Stage IV, the battery ruptures, with all the stored energy releasing instantly due to internal short circuit. Pinholes on the separator surface are observed after dissembling the batteries that are overcharged to 150% SOC or more.

Battery cell capacity loss is extensively studied so as to extend battery life in varied applications from portable consumer electronics to energy storage devices. Battery packs are constructed especially in energy storage devices to provide sufficient voltage and capacity. However, engineering practice indicates that battery packs always fade more critically than cells. We investigate the evolution of battery pack capacity loss by analyzing cell aging mechanisms using the “Electric quantity – Capacity Scatter Diagram (ECSD)” from a system point of view. The results show that cell capacity loss is not the sole contributor to pack capacity loss. The loss of lithium inventory variation at anodes between cells plays a significant role in pack capacity evolution. Therefore, we suggest more attention could be paid to the loss of lithium inventory at anodes in order to mitigate pack capacity degradation.