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Gas distribution of proton exchange membrane fuel cells (PEMFCs) is mainly decided by flow field of bipolar plate. The improper design of distributing channel, nonuniform gas flow distribution and current density distribution among different straight channels are the leading factors that could tremendously undermine the performance and life expectancy of the cell. However, there is lack of research focusing on distributing channel in straight-parallel flow field. In this work, a three-dimensional numerical model of PEMFC cathode flow field is developed with CFD method to investigate the effects of configuration type and width of the distributing channel on pressure distribution in distributing channel and on reactant flow distribution, pressure drop and concentration distribution in multiple straight channel. Effects of electrochemical reaction and formation of water on the flow distribution are taken into consideration.

Proton exchange membrane fuel cells (PEMFC), which convert the chemical energy into electrical energy directly through electrochemical reactions, are widely considered as one of the best power sources for new energy vehicles (NEV). Some of the major advantages of a PEMFC include high power density, high energy conversion efficiency, minimum pollution, low noise, fast startup and low operating temperature. The Membrane Electrode Assembly (MEA) is one of the core components of fuel cells, which composes catalyst layers (CL) coated proton exchange membrane (PEM) and gas diffusion layers (GDL). The performance of MEA is closely related to mass transportation and the rate of electrochemical reaction. The MEA plays a key role not only in the performance of the PEMFCs, but also for the reducing the cost of the fuel cells, as well as accelerating the commercial applications. Commercialized large-size MEA directly plays a major role in determining fuel cell stack and vehicle performance.

Proton Exchange Membrane Fuel Cell (PEMFC) uses hydrogen and oxygen for fuel, the whole energy conversion process almost has no negative impact on the environment. The PEM fuel cell stack with the advantages of low-operating temperature, high current density and fast start-up ability is considered to be the next generation of new electric vehicle power. However, due to the limited current output, it is difficult for a single cell to meet the practical application requirements. The actual fuel cell stack is formed by many single cells assembled together. The assembly process is often related to load transfer, material transfer, energy exchange, multi-phase flow, electrochemical reaction and other factors. The performance of MEA (Membrane Electrode Assembly), sealing gaskets and other components will change during the assembly process, which makes the fuel cell stack assembly process more complex.

Due to coupling of in-wheel motor and wheel/tire, the electric wheel system of in-wheel motor driven vehicle is different from tire suspension system of internal combustion engine vehicle both in the excitation source and structural dynamics. Therefore emerging dynamic issues of electric wheel arouse attention. Longitudinal vibration problem of electric wheel system in starting condition is studied in this paper. Vector control system of permanent magnet synchronous hub motor considering dead-time effect of the inverter is primarily built. Then coupled longitudinal-torsional vibration model of electric wheel system is established based on rigid ring model and dynamic tire/road interface. Inherent characteristics of this model are further analyzed. The vibration responses of electric wheel system are simulated by combining electromagnetic torque and the vibration model. The results indicate that abrupt changes of driving torque will cause transient vibration of electric wheel system.

Startup from subzero temperature is one of the major challenges for polymer electrolyte membrane fuel cell (PEMFC) to realize commercialization. Below the freezing point (0°C), water will freeze easily, which blocks the reactant gases into the reaction sites, thus leading to the start failure and material degradation. Therefore, for PEMFC in vehicle application, finding suitable ways to reach successful startup from subfreezing environment is a prerequisite. As it’s difficult and complex for experimental studies to measure the internal quantities, mathematical models are the effective ways to study the detailed transport process and physical phenomenon, which make it possible to achieve detailed prediction of the inner life of the cell. However, review papers only on cold start numerical models are not available. In this study, an extensive review on cold start models is summarized featuring the states and phase changes of water, heat and mass transfer.

The proton exchange membrane fuel cell (PEMFC) system has emerged as the state-of-art power source for the electric vehicle, but the widespread commercial application of fuel cell vehicle is restricted by its short service life. An enabling high accuracy model holds the key for better understanding, simulation, analysis, subsystem control of the fuel cell system to extract full power and prolong the lifespan. In this paper, a quasi-dynamic lumped parameters model for a 3kW stack is introduced, which includes filling-and-emptying volume sub-models for the relationships between periphery signals and internal states, static water transferring sub-model for the membrane, and empirical electrochemical sub-model for the voltage response. Several dynamic experiments are carried out to identify unknown parameters of the model.

Fuel cell vehicles (FCV) have become a promising transportation tool because of their high efficiency, fast response and zero-emission. However, the cold start problem is one of the main obstacles to limit the further commercialization of FCV in cold weather countries. Many efforts have made to improve the cold start ability. This review presents comprehensive heating methods and influence factors of the research progress in solving the Proton Exchange Membrane Fuel Cells (PEMFC) system cold start problems with more than 100 patents, papers and reports, which may do some help for PEMFC system cold start from the point of practical utilization. Firstly, recent achievements and goals will be summarized in the introduction part. Then, regarding the heating strategies for the PEMFC system cold start, different heating solutions are classified into self-heating strategies and auxiliary-heating heating depending on their heating sources providing approach.

Engine start while driving is one of the most typical and frequent work conditions for hybrid vehicles. Engine start has very significant impact on the driving comfort. Engine start, especially a dynamical engine start, have high control requirements regarding control time, torque output and riding comfort. In some hybrid transmissions such as P2, engine is cranked and synchronized through wet clutch slipping. Because clutch pressure control has time-varying delay and estimation precision of engine torque by ECU (Engine Control Unit) is poor, conventional PID controller is unable to meet the high requirements of control quality. A new control algorithm is proposed in this paper to cope with all these challenges. The new control algorithm is based on LADRC (Linear Active Disturbance Rejection Controller) and is improved through combination with Smith predictor and Adaline network. LADRC is adopted to reduce negative effects of poor precision of engine torque.

With the increasing worldwide concern on environmental pollution, battery electrical vehicles (BEV) have attracted a lot attention. However, it still couldn’t satisfy the market requirements because of the low battery power density, high cost and long charging time. The range-extended electrical vehicle (REEV) got more attention because it could avoid the mileage anxiety of the BEVs with lower cost and potentially higher efficiency. When internal combustion engine (ICE) works as the power source of range extender (RE) for REEV, its NVH, emissions in starting process need to be optimized. In this paper, a 2-cylinder PFI gasoline engine and a permanent magnet synchronous motor (PMSM) are coaxially connected. Meanwhile, batteries and load systems were equipped. The RE co-control system was developed based on Compact RIO (Compact Reconfigurable IO), Labview and motor control unit (MCU).

Water and thermal management is an essential issue that influences performance and durability of a polymer electrolyte membrane fuel cell (PEMFC). Water content in membrane decides its ionic conductivity and membrane swelling favors the ionic conductivity, resulting in decreases in the membrane’s ohmic resistance and improvement in the output voltage. However, if excessive liquid water can’t be removed out of cell quickly, it will fill in the pores of catalyst layer (CL) and gas diffusion layer (GDL) then flooding may occur. It is essential to keep the water content in membrane at a proper level. In this work, a transient isothermal one-dimensional model is developed to investigate effects of the relative humidity of inlet gas and cell temperature on performance of a PEMFC.

Proton exchange membrane fuel cell (PEMFC) system is expected to be the next generation vehicle powertrain. However, water management is still the main problem which directly affects the performance, reliability and durability in PEMFC system. To ensure the accurate water content estimation, High Frequency Resistance (HFR) is the most representative indicator in laboratory. The HFR is calculated by detecting the Alternating Current (AC) voltage response of fuel cell under the excitation of 1k Hz AC current. The voltage level of the AC excitation affects the measurement of HFR. Generally, 5mV AC excitation is used to measure HFR for the fuel cell with an output voltage between 0.6-1V. So, online HFR monitor is a big challenge for vehicle application, due to its low Signal/Noise Ratio (S/N), poor Electromagnetic Compatibility (EMC) environment, high common mode voltage and several hundred cells. In this work, an online fuel cell HFR monitor controller is developed.

It is very important to investigate how road irregularity excitation will affect the durability, reliability, and performance degradation of fuel cell vehicle powertrain and its key components, including the electric motor, power control unit, power battery package and fuel cell engine system. There are very few published literatures in this research area. In this paper, an elementary but integrated experimental work is described, including the real road load sample on proving ground, road load reproduction on vibration test rig, total vehicle road simulation test and key components vibration tests. Remote parameter control technology is adopted to reproduce the real road load on road simulator and six-degree-of-freedom vibration table, which is used respectively for total vehicle and components vibration tests.

The vehicular fuel cell stack is unavoidably impacted by the vibration in the real-world usage due to the road unevenness. However, effects of vibration on stacks have yet to be completely understood. In this work, the mechanical integrity and gas-tightness of the stack were investigated through a strengthen road vibration test with a duration of 200 h. The excitation signals applied in the vibration test were simulated by the acceleration of the stack, which were previously measured in a vehicle vibration test. The load signals of the vehicle vibration test were iterated through a road simulator from vehicle acceleration signals which were originally sampled in the proving ground. Frequency sweep test was conducted before and after the vibration test. During the vibration test, mechanical structure inspection and pressure maintaining test of the stack were conducted at regular intervals.

Most of the existing energy management strategies for Extended-Range Electric Vehicles (E-REVs) are heuristic, which restricts coordination between the battery and the Range Extender. This paper presents an instantaneous optimization energy management strategy based on the Minimum Loss Power Algorithm (MLPA) for a fuel cell E-REV. An instantaneous loss power function of power train system is constructed by considering the charge and discharge efficiency of the battery, together with the working efficiency of the fuel cell Range Extender. The battery working mode and operating points of the fuel cell Range Extender are decided by an instantaneous optimization module (an artificial neural network) that aims to minimize the loss power function at each time step.

To promote the development of automated vehicles (AVs), large scale of field operational tests (FOTs) were carried out around the world. Applications of naturalistic driving data should base on correlative scenarios. However, most of the existing scenario typologies, aiming at advanced driving assistance system (ADAS) and extracting discontinuous fragments from driving process, are not suitable for AVs, which need to complete continuous driving tasks. In this paper, a systematic scenario-typology consisting of four layers (from top to bottom: trip, cluster, segment and process) was first proposed. A trip refers to the whole duration from starting at initial parking space to parking at final one. The basic units ‘Process’, during which the vehicle fulfils only one driving task, are classified into parking process, long-, middle- and short-time-driving-processes. A segment consists of two neighboring long-time-driving processes and a middle or/and short one between them.

Proton exchange membrane fuel cell (PEMFC) has attracted extensive attention in recent years because of its high efficiency and zero emission. Although fuel cell technology has made great progress, durability is still the bottleneck of its large-scale commercialization. In order to systematically study the degradation of fuel cell system for transportation applications, we selected the most severe operating condition - on-off cyclic condition as the research object, and focused on the influence of cell temperature and air relative humidity on the degradation rate of fuel cell by means of polarization curve, reference voltage and CV. The results show that with the same temperature, the fuel cell performance degradation rate first decreases and then increases with the decrease of humidity, which may be due to the increase of platinum ion transfer rate at high relative humidity and the dry membrane at low relative humidity.

The accelerated global progress in the research and development of automobile products, and the use of new technologies, such as the Internet, cloud computing and big data, to coordinate development platforms in different regions and fields, can reduce the duration and cost of development and testing. Specifically, in the context of the current coronavirus disease (COVID-19) pandemic, which has caused great obstacles to normal logistics and transportation, personnel exchanges and information communication, platforms that can support global operation are significant for product testing and validation, because they eliminate the need for the transportation of personnel and equipment. Therefore, the establishment of a distributed test and validation platform for automotive powertrain systems, which can integrate software and hardware testing, is important in terms of both scientific research and industrialization.

A three-dimensional two-phase single-channel purge mode of proton exchange membrane fuel cell was established, and the steady-state and purge process were simulated. The water distribution in fuel cell after steady-state operation was studied. The changing trend of water content and water volume fraction under co-flow/counter-flow purge conditions was also studied. The results show that the membrane water content and water volume fraction under the ridge position of the fuel cell is more than the flow channel. The non-uniform distribution of membrane water along the direction of the flow channel is significant in co-flow, and the difference can be up to 6. In addition, the effects of different working conditions on purge were studied. It was found that in the purge condition, the water content of the inner membrane of 120s could be basically reduced to below 3.

In recent years, intelligent driving technology is being extensively studied. This paper proposes a path planning method for perpendicular parking based on vehicle kinematics model using MPC optimization, which aims to solve the perpendicular parking task. Firstly, in the case of any initial position and orientation of the vehicle, judging whether the vehicle can be parked at one step according to the location of the parking place and the width of the lane, and then calculating the starting position for parking, and use the Bezier curve to connect the initial position and the starting position. Secondly, reference parking path is calculated according to the collision constraints of the parking space. Finally, because the parking path based on the vehicle kinematics model is composed of circle arcs and straight lines, the curvature of the path is discontinuous. The reference parking path is optimized using Model Predictive Control (MPC).

Durability performance prediction is a critical issue in fuel cell research. During the demonstration operation of fuel cell commercial vehicles in China, this issue has attracted more attention. In this article, the long short-term memory neural network (LSTMNN), which is an improved recurrent neural network (RNN), and the demonstration operation data are used to establish the prediction model to predict the durability performance of the fuel cell stack. Then, a model based on a back-propagation neural network (BPNN) is established to be a control group. The demonstration operation data is divided into training group and validation group. The former is used to train the prediction model, and the latter is used to verify the validity and accuracy of the prediction model. The outputs of the prediction model, as the durability performance evaluation indexes of the fuel cell, are the polarization curve (current-voltage curve) and the voltage decay curve (time-voltage curve).