World Electr. Veh. J., Volume 12, Issue 3 (September 2021) – 71 articles

In the years to come, Connected and Automated Vehicles (CAVs) are expected to substantially improve the road safety and environmental impact of the road transport sector. The information from the sensors installed on the vehicle has to be properly integrated with data shared by the road infrastructure (smart road) to realize vehicle control, which preserves traffic safety and fuel/energy efficiency. In this context, the present work proposes a real-time implementation of a control strategy able to handle simultaneously motion and hybrid powertrain controls. This strategy features a cascade of two modules, which were implemented through the model-based design approach in MATLAB/Simulink. The first module is a Model Predictive Control (MPC) suitable for any Hybrid Electric Vehicle (HEV) architecture, acting as a high-level controller featuring an intermediate layer between the vehicle powertrain and the smart road. The MPC handles both the lateral and longitudinal vehicle dynamics, acting on the wheel torque and steering angle at the wheels. It is based on a simplified, but complete ego-vehicle model, embedding multiple functionalities such as an adaptive cruise control, lane keeping system, and emergency electronic brake. The second module is a low-level Energy Management Strategy (EMS) of the powertrain realized by a novel and computationally light approach, which is based on the alternative vehicle driving by either a thermal engine or electric unit, named the Efficient Thermal Electric Skipping Strategy (ETESS). The MPC provides the ETESS with a torque request handled by the EMS module, aiming at minimizing the fuel consumption. The MPC and ETESS ran on the same Microcontroller Unit (MCU), and the methodology was verified and validated by processor-in-the-loop tests on the ST Microelectronics board NUCLEO-H743ZI2, simulating on a PC-host the smart road environment and a car-following scenario. From these tests, the ETESS resulted in being 15-times faster than than the well-assessed Equivalent Consumption Minimization Strategy (ECMS). Furthermore, the execution time of both the ETESS and MPC was lower than the typical CAN cycle time for the torque request and steering angle (10 ms). Thus, the obtained result can pave the way to the implementation of additional real-time control strategies, including decision-making and motion-planning modules (such as path-planning algorithms and eco-driving strategies). Full article

A lithium titanate oxide (LTO) anode based battery has high power density, and it is widely applied in transportation and energy storage systems. However, the thermal performance of LTO anode based battery module is seldom studied. In this work, a heat generation theoretical model of the battery is explored. The thermal performance of LTO anode based battery modules under high discharge rates is studied by both experiment and simulation. It is found that the temperature rise of the battery can be estimated accurately with the calculation of the equivalent internal resistance under different discharge rates. In addition, under the same depth of discharge, both the temperature rise and the temperature difference in the battery module increase with the discharge rates. Full article

Dynamic wireless power transfer (DWPT) technology shows a vast development prospect for EV application, with advantages of reducing the demand for battery capacity and improving the user experience. However, the need to improve output performance leads to a challenge in receiver design with limited space and allowable load on the EV side. In this paper, a design of a dual-phase non-salient pole (NSP) receiver for the EV DWPT system with bipolar transmitter is proposed, aiming at providing a solution to the contradiction between reducing the volume or cost and improving the misalignment tolerance of the receiver. The coupling principle of the proposed receiver is analyzed. The structure parameters are optimized by the finite-element simulation method. Combined with specific design indexes, it is proven by comparison with the existing dual-phase receiver that the proposed receiver is 35.4% smaller in volume and needs 47.0% shorter wires. Moreover, the significant advantage of the proposed dual-phase NSP receiver in misalignment tolerance is verified by simulations and experimental comparisons. Full article

The global electric vehicle (EV) is expanding enormously, foreseeing a 17.4% increase in compound annual growth rate (CAGR) by the end of 2027. The lithium-ion battery is considered as the most widely used battery technology in EV. The accurate and reliable diagnostic and prognostic of battery state guarantees the safe operation of EV and is crucial for durable electric vehicles. Research focusing on lithium-ion battery life degradation has grown more important in recent years. In this study, a model built for state of health (SoH) estimation for the LTO anode-based lithium-ion battery is presented. First, electrochemical impedance spectroscopy (EIS) is used to study the deterioration in battery performance, measurements such as charge transfer resistance and ohmic resistance are analyzed for different operational conditions and selected as key characteristic parameters for the model. Then, the model based on a backpropagation neural network (BPNN) along with the characteristic parameters is trained and validated with a real-life driving profile. The model shows a relatively accurate estimation of SoH with a mean-squared-error (MSE) of 0.002. Full article

This paper proposes a decentralized control approach using a co-simulation platform to monitor protective elements and provide complete protection scheme for distribution systems. Real time measurements are obtained by interfacing the system model in RSCAD/RTDS with SEL 421 protective relays and publish/subscribe the voltage and current signals of the buses and transmission lines based on IEC 61850 communication protocol to isolate the fault correctly. The proposed technique helps to identify the location of the fault and introduces primary and buck protection for the system. The communication networks assists in facing cyber and physical threats and finding a new path for healthy relays to remove faults from the system. This technique is investigated on an IEEE 14 bus system for all possible fault locations. The proposed scheme can clear the fault by isolating the minimum part of the system and improving the endurance of the power in it. The system shows the smooth information flow between the cyber and physical parts to isolate faults in it in different cases. Full article

To address the power distribution problem that occurs in hybrid energy storage systems (HESSs) in electric vehicles, a fuzzy control distribution method is proposed in this paper, taking the vehicle demand power; supercapacitor power, P_SC;; and lithium battery power, P_bat, as the inputs and the power distribution factor of the supercapacitor as the output to control the power distribution of the composite energy storage system, in addition to dividing the whole working condition into three time scales, namely, long, medium and short. In this study, we conducted a comprehensive analysis and comparison with typical control methods regarding the energy storage element output power, battery state of charge (SOC) change, energy flow diagram and power frequency. The simulation experiment results show that the proposed strategy is more effective in reducing the peak output power of the power battery, improving the effective power utilization rate of HESS and the effective energy utilization rate. In order to further verify the effectiveness of the control strategy, a pure electric bus power system test bench was built based on similar principles, and a representative time period under the driving conditions of the China city bus (CHTC-B) was selected, involving an acceleration process from 30 to 48 s (process 1), a uniform speed process from 636 to 671 s (process 2) and a regenerative braking process from 1290 to 1304 s (process 3), further verifying the effectiveness and feasibility of the proposed control strategy. Full article

In order to improve the stability of vehicle steering on low-adhesion road surfaces, this paper designed a hybrid robust control strategy, H₂/H_∞, for active front-wheel steering (AFS) based on robust control theory. Firstly, we analyzed the influence of the sidewall stiffness and road adhesion coefficient of the tires on vehicle stability, through which we can study the wheel deflection characteristics of low-adhesion roads. Secondly, the reference yaw velocity of the vehicle was calculated using the three-degrees-of-freedom model as the reference model, through which, taking the norm H_∞ as the objective function and the norm H₂ as the limit to control the output, the hybrid robust control strategy H₂/H_∞ of the AFS system on a low-adhesion road surface was developed. Finally, the simulation experiment was carried out by the Simulink/CarSim co-simulation platform and a hardware-in-the-loop (HIL) experiment. In this paper, the results show that the AFS control strategy can improve the vehicle handling stability on low-adhesion road surfaces, and the controller has good path tracking performance and robustness. Full article

For electric vehicles (EVs) to realise the UK government’s goal of mass-market dominance, there are surmountable hurdles to resolve before car users accept this radical shift in motoring technology. This study focuses on recent EV adopters who experience a new phenomenon described as charge point trauma (CPT). In contrast to range anxiety, we define CPT as the psychological, physiological, and behavioural condition where EV user’s experiences develop trauma or anxiety in response to the availability of sufficient charge points, locations, payment processes, and operability. Resolving impediments to EV usage reduces long-term growth barriers, which we argue can subsequently lower or even eliminate EV driver anxiety. We conclude that range anxiety still plays a major part in overall EV driver trauma, and after deep analysis of our case study data conclude that a trauma other than range anxiety exists at the charge point. To mitigate this phenomenon, we propose a regulatory framework comprising a series of stimuli to encourage EV uptake. These recommendations should be targeted at regulating a new generation of EV charging stations to meet operational parity with current fossil fuel filling stations by ensuring they are always on, available in sufficient numbers, accessible and operable as part of the UK motorway and major trunk network. This will de-risk EV purchasing and stimulate their adoption in this embryonic stage, reducing CPT in the process. Full article

Electrified vehicles (xEV), especially the battery electric vehicle (BEV), are burgeoning and growing fast in China, aimed at building a sustainable, carbon-neutral future. This work presents an overview and quantitative comparison of the carbon-neutral vehicles fuel options based on the well-to-wheel (WTW) analysis. A more intuitionistic figure demonstrates the fuel options for greenhouse gas (GHG) emissions and describes the sustainability. Electricity and hydrogen shift the tailpipe emissions to the upstream process, forming larger WTW emissions from a fuel cycle view. The electricity WTW GHG emission reaches as much as twice that of gasoline. However, the high efficiency of the electric drive system improves the WTW emission performance from a vehicle view, making the lowest WTW emission of BEV. The fuel options’ technical and environmental perspectives are presented. Finally, long-term carbon-neutral vehicle development is discussed. Full article

Four-wheel independent drive electric vehicles have become the latest development trend of electric vehicles due to their simple structure and high control accuracy. Aiming at the sliding problem of four-wheel independent driving electric vehicles in the driving process, a driving anti-skid control strategy is designed. The strategy includes two contents: (1) a road recognition module that tracks the best slip rate in real time; (2) a slip rate control module that uses fuzzy PID control. Then, based on Carsim and MATLAB/Simulink, the vehicle dynamics model, tire model and driving anti-skid control model are established. A simulation of the driving anti-skid control algorithm is carried out to verify the feasibility of the control strategy. Finally, based on the built-up dSPACE semi-physical experimental simulation platform, the verification was carried out, and the test and simulation results were compared to verify the effective feasibility of the driving anti-skid control strategy. Full article

In this study, the back electromotive force (EMF) waveforms of a flux switching permanent magnet (FSPM) machine and variable flux memory permanent magnet (VFMPM) machine with same main dimension were researched. Firstly, the simulation result showed that the maximum amplitude of phase back EMF waveform of FSPM machine was 245% larger than that of the VFMPM machine, and this was verified by the experimental result (243%). Secondly, the phase back EMF harmonics of the FSPM machine and VFMPM machine were compared, including the enhance flux condition and weaken flux condition of VFMPM machine. At last, the mutual demagnetization effect, which led to the difference amplitudes of maximum back EMF waveform between FSPM machine and VFMPM machine was analyzed. The comparison and analysis of the back EMF waveform will provide some qualitative advice for the future application research of the FSPM machine and VFMPM machine, such as application selection, optimization control method and so on. Full article

A collaborative design for the uneven distributions of a flow channel, gas diffusion layer porosity and catalyst layer porosity are newly proposed to improve the utilization ratio of the membrane electrode assembly of the proton exchange membrane fuel cell. The effects of the uneven design of the rib width and of the uneven porosity parameters of the cathode and anode gas diffusion layer and catalyst layer on the fuel cell performance were studied in detail. Numerical simulations were designed and implemented for validation. The results show that the fuel cell performance could be improved through the collaborative design of uneven distributions for different layers. The rib width gradually decreasing and the porosity of the cathode gas diffusion layer and the cathode catalyst layer gradually increasing along the fluid flow direction would contribute to a better design compared to the regular even design. The new uneven design can make the fuel penetrate into the catalyst layer in time to participate in the reaction, improve the utilization rate of the membrane electrode assembly, and greatly improve the performance of the fuel cell. Full article

This article reviews the Volvo Low-Impact Heavy Green Transport Solution (LIGHTS) project, a multifaceted public–private partnership in Southern California, and provides some early insights and a model for successful fleet adoption of Class 8 battery-electric trucks. This paradigm shift in commercial trucking is emerging, forcing greater interdependence among many stakeholders—fleets, truck manufacturers, and policymakers—not currently engaged in the traditional heavy-duty commercial truck market. The many perspectives from this article such as lead times and costs associated with the deployment of charging infrastructure, developing the workforce to support largescale deployments, and the need for market development incentives from the government can be used to inform the programs and policies of California and other states seeking to follow their lead. Full article

The construction of hydrogen refueling stations is an important part of the promotion of fuel cell vehicles. In this paper, a multi-period hydrogen refueling station location model is presented that can be applied to the planning and construction of hydrogen infrastructures. Based on the hydrogen demand of fuel cell passenger cars and commercial vehicles, the model calculates the hydrogen demand of each zone by a weighting method according to population, economic level and education level. Then, the hydrogen demand of each period is calculated using the generalized Bass diffusion model. Finally, the set covering model is improved to determine the locations of the stations. The new model is applied to the scientific planning of hydrogen refueling stations in Jiading District, Shanghai; the construction location and sequence of hydrogen refueling stations in each period are given, and the growth trend of hydrogen demand and the promoting effect of hydrogen refueling stations are analyzed. The model adopted in this model is then compared with the other two kinds of node-based hydrogen refueling station location models that have previously been proposed. Full article

Getting accurate lifetime predictions for a particular cell chemistry remains a challenging process, largely dependent on time and cost-intensive experimental battery testing. This paper proposes a transfer learning (TL) method to develop LIB ageing models, which allow for the leveraging of experimental laboratory testing data previously obtained for a different cell technology. The TL method is implemented through Neural Networks models, using LiNiMnCoO₂/C laboratory ageing data as a baseline model. The obtained TL model achieves an 1.01% overall error for a broad range of operating conditions, using for retraining only two experimental ageing tests of LiFePO₄/C cells. Full article

In recent years, battery-swapping heavy-duty trucks have seen rapid growth in China. Summarizing from the practical experiences gained in this development, and starting from market research and analysis of the most typical city of application case, Beijing, we aim to achieve the following: (ⅰ) Establish an operating cost model for battery-swapping heavy-duty trucks throughout a full operation cycle from the perspective of a heavy-duty truck freight transport capacity operator, based on four key cost dimensions, including transportation equipment, operation and maintenance, environmental protection compensation, and battery recycling compensation. (ⅱ) Calculate and compare the operating cost economy of battery-swapping heavy-duty trucks and other types of heavy-duty truck under different energy supplement modes, including charging, hydrogenation, and diesel. (ⅲ) Propose suggestions for faster and more successful heavy-duty truck electrification. The results indicate that battery-swapping heavy-duty trucks have good cost economy in a full operation cycle under specific scenario, and their economy will be improved with the popularization of battery-swapping stations. Full article

Aiming at the accelerated aging problem that may occur during the use of high specific energy lithium-ion batteries, this article proposes a method to judge the accelerated aging of lithium-ion batteries. Taking the IC curve and DV curve as the starting point, the complete characteristic curve of the new battery is used as a comparison benchmark, and the battery characteristic curves of different aging stages are compared and analyzed, and the parameters that have obvious changes before and after the accelerated aging of the battery are extracted as the characteristics that the battery has accelerated aging. It is important to establish the relevant characteristic parameter matrix, and use the logistic regression method to train the accelerating aging model of the battery to realize the diagnosis of accelerating aging fault. In view of the fact that lithium batteries rarely undergo a complete charging process, the characteristic parameter sets established in this paper are based on the IC curve and the DV curve in the 15–75% SOC range, which have certain practicability. Full article

With the promotion and financial subsidies of the new energy vehicle (NEV), the NEV industry of China has developed rapidly in recent years. However, compared with traditional fuel vehicles, the technological maturity of the NEV is still insufficient, and there are still many problems that need to be solved in the R&D and operation stages. Among them, energy consumption and driving range are particularly concerning, and are closely related to the driving style of the driver. Therefore, the accurate identification of the driving style can provide support for the research of energy consumption. Based on the NEV high-frequency big data collected by the vehicle-mounted terminal, we extract the feature parameter set that can reflect the precise spatiotemporal changes in driving behavior, use the principal component analysis method (PCA) to optimize the feature parameter set, realize the automatic driving style classification using a K-means algorithm, and build a driving style recognition model through a neural network algorithm. The result of this paper shows that the model can automatically classify driving styles based on the actual driving data of NEV users, and that the recognition accuracy can reach 96.8%. The research on driving style recognition in this paper has a certain reference value for the development and upgrade of NEV products and the improvement of safety. Full article

This paper proposes a desktop wireless power transfer system that can wirelessly supply power to electrical equipment in a certain space above the aluminum foil using only a high-frequency electric field. Compared with other wireless power supply systems, this system has a smaller power receiving device and a wider power supply range, which is convenient for wireless power supply of portable electrical equipment and low-power electric vehicles. The power receiving device of the system is only the size of a mobile phone, and the power supply range can reach 1.2 m². This article introduces the system design, electromagnetic field simulation and experiment of the desktop wireless power transfer system. The experimental results show that by using a mobile phone-sized receiving device to connect a light bulb and a fan, multiple loads can simultaneously receive power in a specific space above the desktop power supply. In addition, people can hold the power receiving device for wireless charging. Full article

In the practical application of wireless power transfer (WPT), the identification of the secondary coil and the analysis of the space magnetic field of the coil will affect the matching scheme of the coil, which will further affect the performance of energy transmission. At present, the establishment of the coil space magnetic field model mainly adopts the finite element method (FEM). The accuracy of the results is limited by the computer performance and the specific settings during calculation, which usually takes a long time. Additionally, it can only analyze and establish the space magnetic field of the coil with specific parameters. Especially when the coil structure and parameters change, it is difficult to quickly establish the spatial magnetic field. This paper presents a secondary side coil identification method of a wireless charging system based on the magnetic field cloud image characteristics. The image feature extraction algorithm is used to extract features of a certain height magnetic field cloud image of an unknown structure type coil obtained by FEM. Further, by matching with the characteristics of the magnetic field cloud image of the known coil, the identification of the unknown coil structure type is realized. The effectiveness and accuracy of the proposed method is verified by an example. This algorithm is helpful to extract the characteristics of the coil space magnetic field, and can establish coil space magnetic field models with different structure types and different coil parameters combined with deep learning to guide the matching scheme of the primary and secondary coils, and realize efficient energy transmission. Full article

In recent years, electric vehicles have achieved rapid development. Intelligence is one of the important trends to promote the development of electric vehicles. As a result, autonomous driving system is becoming one of the core systems of electric vehicles. Considering that environmental perception is the basis of intelligent planning and safe decision-making for intelligent vehicles, this paper presents a survey of the existing perceptual methods in vehicles, especially 3D object detection, which guarantees the reliability and safety of vehicles. In this review, we first introduce the role of perceptual module in autonomous driving system and a relationship with other modules. Then, we classify and analyze the corresponding perception methods based on the different sensors. Finally, we compare the performance of the surveyed works on public datasets and discuss the possible future research interests. Full article

The global market of electric vehicles has become one of the prime growth industries of the 21st century fueled by marketing efforts, which frequently assert that electric vehicles are “very efficient” and “produce no pollution.” This article uses thermodynamic analysis to determine the primary energy needs for the propulsion of electric vehicles and applies the energy/exergy trade-offs between hydrocarbons and electricity propulsion of road vehicles. The well-to-wheels efficiency of electric vehicles is comparable to that of vehicles with internal combustion engines. Heat transfer to or from the cabin of the vehicle is calculated to determine the additional energy for heating and air-conditioning needs, which must be supplied by the battery, and the reduction of the range of the vehicle. The article also determines the advantages of using fleets of electric vehicles to offset the problems of the “duck curve” that are caused by the higher utilization of wind and solar energy sources. The effects of the substitution of internal combustion road vehicles with electric vehicles on carbon dioxide emission avoidance are also examined for several national electricity grids. It is determined that grids, which use a high fraction of coal as their primary energy source, will actually increase the carbon dioxide emissions; while grids that use a high fraction of renewables and nuclear energy will significantly decrease their carbon dioxide emissions. Globally, the carbon dioxide emissions will decrease by approximately 16% with the introduction of electric vehicles. Full article

Automobile safety driving technology is a hot topic in today’s society, which is very significant to the social transportation system. Vehicle driving behavior monitoring is the foundation and core of safe driving techniques. The research on existing vehicle safety technology can not only improve the understanding of current safe driving research progress, but also provide reference for future researchers. This paper proposes a state recognition system based on a three-dimensional convolutional neural network, which can identify several improper states frequently encountered by drivers during driving, including drinking, making phone calls, and smoking, and can also issue alarm interventions. The system takes the collected continuous video frame information as the input of the three-dimensional convolutional network, carries out multi-level feature extraction and spatio-temporal information fusion, and identifies the driver state according to the extracted spatio-temporal features. The state is judged by the facial feature points of the video stream, and the design of the video surveillance driver state recognition system is completed. Then, the driver status recognition is improved and optimized, and finally, the actual deployment of the driver status recognition system on the mobile terminal is completed. A large number of experimental results show that the driver status recognition system proposed in this paper has achieved upper identification accuracy. Full article

In this paper, a kind of on-board liquid hydrogen (LH₂) cold energy utilization system for a heavy-duty fuel cell hybrid truck is proposed. Through this system, the cold energy of LH₂ is used for cooling the inlet air of a compressor and the coolant of the accessories cooling system, sequentially, to reduce the parasitic power, including the air compressor, water pump, and radiator fan power. To estimate the cold energy utilization ratio and parasitic power saving capabilities of this system, a model based on AMESim software was established and simulated under different ambient temperatures and fuel cell stack loads. The simulation results show that cold energy utilization ratio can keep at a high level except under extremely low ambient temperature and light load. Compared to the original LH₂ system without cold energy utilization, the total parasitic power consumption can be saved by up to 15% (namely 1.8 kW). Full article

In order to solve the problems of difficulty and long times to pick up cars in complex traffic scenes, this paper proposes an intelligent networked car-hailing system in complex scenes based on multi sensor fusion and Ultra-Wide-Band (UWB) technology. UWB positioning technology is adopted in the system, and the positioning data is optimized by the untraceable Kalman filter algorithm. Based on the environment perception technology of multi sensor fusion, such as machine vision and laser radar technology, an anti-collision warning algorithm was proposed in the process of car-hailing, which improved the safety factor of car-hailing. When the owner enters the parking lot, the intelligent vehicle can automatically locate the owner’s position and drive to the owner without human intervention, which provides a new idea for the development of intelligent networked vehicles and effectively improves the navigation accuracy and intelligence of intelligent vehicles. Full article

Deep learning has made great advances in the field of image processing, which allows automotive devices to be more widely used in humans’ daily lives than ever before. Nowadays, the mobile robot navigation system is among the hottest topics that researchers are trying to develop by adopting deep learning methods. In this paper, we present a system that allows the mobile robot to localize and navigate autonomously in the accessible areas of an indoor environment. The proposed system exploits the Convolutional Neural Network (CNN) model’s advantage to extract data feature maps for image classification and visual localization, which attempts to precisely determine the location region of the mobile robot focusing on the topological maps of the real environment. The system attempts to precisely determine the location region of the mobile robot by integrating the CNN model and topological map of the robot workspace. A dataset with small numbers of images is acquired from the MYNT EYE camera. Furthermore, we introduce a new loss function to tackle the bounded generalization capability of the CNN model in small datasets. The proposed loss function not only considers the probability of the input data when it is allocated to its true class but also considers the probability of allocating the input data to other classes rather than its actual class. We investigate the capability of the proposed system by evaluating the empirical studies based on provided datasets. The results illustrate that the proposed system outperforms other state-of-the-art techniques in terms of accuracy and generalization capability. Full article

The gas diffusion layer (GDL) plays an important role in the mass transfer process during proton exchange membrane fuel cell (PEMFC) operation. However, the GDL porosity distribution, which has often been ignored in the previous works, influences the mass transfer significantly. In this paper, a 2D lattice Boltzmann method model is employed to simulate the liquid water transport process in the real GDL (considered porosity distribution) and the ideal GDL (ignore porous distribution), respectively. It was found that the liquid water transport in the real GDL will be significantly affected by the local low porosity area. In the real GDL, a liquid water saturation threshold can be noticed when the contact angle is about 118°. The GDL porosity distribution shows a stronger influence on liquid dynamic than hydrophobicity, which needs to be considered in future GDL modelling and design. Full article

Due to depleting fossil fuel reserves coupled with a climate crisis, sustainability is gaining ground, and electric vehicles (EVs) are emerging to be the new face of this field. However, the idea of EVs will be genuinely sustainable only if they are charged using renewable energy. This paper presents results from the design of a solar-powered EV charging station for an Indian context. PVsyst 7.2 software has been used for the system design. The analysis, based on the number of cars charged annually, the monthly variation in energy generation, the investment cost, and the decrease in carbon dioxide (CO₂) emissions using different module technologies for six Indian cities, has been deliberated. The results indicate that an off-grid 8.1 kWp system with two days of battery autonomy has the fewest unused energy losses, with a good performance ratio (PR). It can completely charge around 414 vehicles of 30 kWh battery capacity annually. This would help to reduce annual CO₂ emissions by approximately 7950 kg. For cities near the equator, maximum energy is produced during March or January, and for cities near the Tropic of Cancer, energy production maximizes during May–June. The overall system has better energy generation and economy when monocrystalline modules are used. Full article

Permanent magnet torque motor (PMTM) is widely used in aerospace, computer numerical control (CNC) machine tools, and industrial robots with many advantages such as high torque density, strong overload capacity, and low torque ripple. With the upgrading of industrial manufacturing, the requirements for the performance of torque motors have become more stringent. At present, how to achieve high output torque and low torque ripple has become a research hotspot of torque motors. In the optimization process, it is necessary to increase the output torque while the torque ripple can be reduced, and it is difficult to get a good result with the single-objective optimization. In this paper, a multi-objective optimization method based on the combination of design parameter stratification and support vector machine (SVM) is proposed. By analyzing the causes of torque ripple, the output torque, efficiency, cogging torque, and total harmonic distortion (THD) of back electromotive force (EMF) are selected as the optimization objectives. In order to solve the coupling problem between the motor parameters, the calculation formula of Pearson correlation coefficient is used to analyze the relationship between the design parameters and the optimization objectives, and the design parameters are layered ac-cording to the sensitivity. In order to shorten the optimization cycle of the motor, SVM is used as a fitting method of the mathematical model. The performance between initial and optimal motors is compared, and it can be found that the optimized motor has a higher torque and lower torque ripple. The simulation results verify the effectiveness of the proposed optimization method. Full article

The hydrogen storage tank is a key parameter of the hydrogen storage system in hydrogen fuel cell vehicles (HFCVs), as its safety determines the commercialization of HFCVs. Compared with other types, the type IV hydrogen storage tank which consists of a polymer liner has the advantages of low cost, lightweight, and low storage energy consumption, but meanwhile, higher hydrogen permeability. A detailed review of the existing research on hydrogen permeability of the liner material of type IV hydrogen storage tanks can improve the understanding of the hydrogen permeation mechanism and provide references for following-up researchers and research on the safety of HFCVs. The process of hydrogen permeation and test methods are firstly discussed in detail. This paper then analyzes the factors that affect the process of hydrogen permeation and the barrier mechanism of the liner material and summarizes the prediction models of gas permeation. In addition to the above analysis and comments, future research on the permeability of the liner material of the type IV hydrogen storage tank is prospected. Full article