Design scheme for fast charging station for electric vehicles with distributed photovoltaic power generation

The demand for fast charging is increasing owing to the rapid expansion of the market for electric vehicles. In addition, the power generation technology for distributed photovoltaic has matured. This paper presents a design scheme for a fast charging station for electric vehicles equipped with distributed photovoltaic power generation system taking the area with certain conditions in Beijing as an example construction site. The technical indexes and equipment lectotype covering the general framework and subsystems of the charging station are determined by analyzing the charging service demand of fast charging stations. In this study, the layout of the station is developed and the operation benefits of the station is analyzed. The design scheme realizes the design objective of "rationalization, modularization and intelligentization" of the fast charging station and can be used as reference for the construction of a fast charging network in urban area.

Optimum Driving System Design for Dual-Motor Pure Electric Vehicles

A pure electric vehicle driven by dual motors is taken as the research object and the driving scheme of the driving motor is improved to increase the transmission efficiency of existing electric vehicles.Based on the architecture of the transmission system,we propose vehicle performance parameters and performance indexes of a pure electric vehicle,a time-sharing driving strategy of dual motors.First,the parameters of the battery,motor,and transmission system are matched.Then,the electric vehicle transmission model is built in Amesim and the control strategy is designed in Simulink.With the optimization goal of improving the vehicle’s dynamic performance and driving range,the optimal parameters are determined through analysis.Finally,the characteristics of the motor are tested on the bench.The results show that the energy-saving potential of the timesharing driven double motor is higher,and the driving mileage of the double motor drive is increased by 4%.

Numerical model of on-road emission rates of diesel buses in Beijing

A total of 14 in-use diesel buses were selected to conduct emission measurement using a portable emissions measurement system （PEMS） in Beijing. Their instantaneous gaseous emission rates, particular matter （PM） emission rates and driving parameters were obtained. The influences of speed, acceleration and vehicle specific power （VSP） on emissions were analyzed. Based on the relationships between these driving parameters and emissions, 24 driving bins defined by speed, ac- celeration and VSP were constructed with cluster analysis to group emission rates for Euro Ⅲ and IV buses, respectively. Then the emissions reductions from Euro Ⅲ to Euro Ⅳ diesel buses were ana- lyzed. Lastly, on-road hot-stabilized emission rate model for diesel buses in Beijing was developed. Through the comparison of the model simulation emission rates with the measured emission rates, the modeled emission results were in good agreement with the measured emission results. In most of the cases, the differences were less than 12 %.

Thermal runaway propagation behavior of the Cell-to-Pack battery system

Structurally compact battery packs significantly improve the driving range of electric vehicles.Technologies like Cell-to-Pack increase energy density by 15%-20%.However,the safety implications of multiple tightly-packed battery cells still require in-depth research.This paper studies thermal runaway propagation behavior in a Cell-to-Pack system and assesses propagation speed relative to other systems.The investigation includes temperature response,extent of battery damage,pack structure deformation,chemical analysis of debris,and other considerations.Results suggest three typical patterns for the thermal runaway propagation process:ordered,disordered,and synchronous.The synchronous propagation pattern displayed the most severe damage,indicating energy release is the largest under the synchronous pattern.This study identifies battery deformation patterns,chemical characteristics of debris,and other observed factors that can both be applied to identify the cause of thermal runaway during accident investigations and help promote safer designs of large battery packs used in large-scale electric energy storage systems.

Review and Development of Electric Motor Systems and Electric Powertrains for New Energy Vehicles

This paper presents a review on the recent research and technical progress of electric motor systems and electric powertrains for new energy vehicles.Through the analysis and comparison of direct current motor,induction motor,and synchronous motor,it is found that permanent magnet synchronous motor has better overall performance;by comparison with converters with Si-based IGBTs,it is found converters with SiC MOSFETs show significantly higher efficiency and increase driving mileage per charge.In addition,the pros and cons of different control strategies and algorithms are demonstrated.Next,by comparing series,parallel,and power split hybrid powertrains,the series-parallel compound hybrid powertrains are found to provide better fuel economy.Different electric powertrains,hybrid powertrains,and range-extended electric systems are also detailed,and their advantages and disadvantages are described.Finally,the technology roadmap over the next 15 years is proposed regarding traction motor,power electronic converter and electric powertrain as well as the key materials and components at each time frame.

An ultra-fast charging strategy for lithium-ion battery at low temperature without lithium plating

Conventional charging methods for lithium-ion battery(LIB)are challenged with vital problems at low temperatures:risk of lithium(Li)plating and low charging speed.This study proposes a fast-charging strategy without Li plating to achieve high-rate charging at low temperatures with bidirectional chargers.The strategy combines the pulsed-heating method and the optimal charging method via precise control of the battery states.A thermo-electric coupled model is developed based on the pseudo-twodimensional(P2D)electrochemical model to derive charging performances.Two current maps of pulsed heating and charging are generated to realize real-time control.Therefore,our proposed strategy achieves a 3 C equivalent rate at 0℃ and 1.5 C at-10℃ without Li plating,which is 10–30 times faster than the traditional methods.The entropy method is employed to balance the charging speed and the energy efficiency,and the charging performance is further enhanced.For practical application,the power limitation of the charger is considered,and a 2.4 C equivalent rate is achieved at 0℃ with a 250 kW maximum power output.This novel strategy significantly expands LIB usage boundary,and increases charging speed and battery safety.

Parameter Study and Improvement of Gearbox Whine Noise in Electric Vehicle

Gearbox whine noise can seriously reduce the interior sound quality in an electric passenger car.In this work,a six-degree-offreedom(6-DOF)dynamic model of a helical gear system was constructed and the mechanism for generation of whine noise was analyzed.The root cause of the problem was found through noise,vibration and harshness(NVH)testing of the gearbox and the vehicle.A rigid-elastic coupling dynamics model of the reducer assembly was then developed.The accuracy of the model was then validated via modal testing.The structure-borne noise of the reducer under full acceleration conditions was predicted using the acoustic structure coupling model and the rigid-elastic coupling model of the reducer.Gear parameters including the pressure angle,the helix angle and the contact ratio were studied to determine their effects on the whine noise.Gear tooth microgeometry modification parameters were then optimized to reduce the transmission error of the first pair of meshing gears.Finally,the whine noise from the gearbox was eliminated.

锂离子电池加速老化:连接电池老化机制分析与寿命预测的桥梁

储能行业和新能源汽车的爆发式增长要求对锂离子电池的老化行为尤其是电池的寿命行为有更加深入的了解.准确地预测电池在各种工作条件下的使用寿命有助于优化电池的实际运行条件和延长电池的使用寿命,最终达到降低电池生命周期内总成本的目的.加速老化是一种经济高效的产品寿命评价方法,可以在短时间内获得大量的电池老化信息,快速预测锂离子电池在各种工作应力下的寿命特征.然而,基于加速老化进行电池寿命预测的前提是电池老化机理的一致性.本文综述了锂离子电池内各部件的老化机理和应力加速条件下的电池衰退机制以及相应的老化模式,为评价电池老化机理的一致性提供了参考.此外,本文还介绍了一些基于加速老化的电池寿命经验预测模型并为今后锂离子电池的加速老化研究提供了一些建议.

Effect of Heat Treatment on Microstructure and Mechanical Properties of Quenching and Partitioning Steel

In order to investigate the effect of microstructural characterization on the mechanical properties and retained austenite stability, a different type of quenching and partitioning steel（I-Q＆P） through intercritical annealing before the quenching and partitioning process was designed, which can realize lamellar intercritical microstructure compared to the conventional quenching and partitioning（Q＆P） process. The morphology of ferrite and martensite/retained austenite is lamellar in the I-Q＆P steel while it is equiaxed after being heat-treated by conventional Q＆P process. The I-Q＆P steel is proved to have better formability and mechanical properties than conventional Q＆P steel, which is due to the highervolume fraction of retained austenite in the I-Q＆P steel and confirmed by electron backscattering diffraction patterns and X-ray diffraction. Furthermore, the stability of retained austenite in I-Q＆P steel is also higher than that in conventional Q＆P steel, which is investigated by tensile tests and differential scanning calorimetry.

Machine learning and neural network supported state of health simulation and forecasting model for lithium-ion battery

As the intersection of disciplines deepens,the field of battery modeling is increasingly employing various artificial intelligence(AI)approaches to improve the efficiency of battery management and enhance the stability and reliability of battery operation.This paper reviews the value of AI methods in lithium-ion battery health management and in particular analyses the application of machine learning(ML),one of the many branches of AI,to lithium-ion battery state of health(SOH),focusing on the advantages and strengths of neural network(NN)methods in ML for lithium-ion battery SOH simulation and prediction.NN is one of the important branches of ML,in which the application of NNs such as backpropagation NN,convolutional NN,and long short-term memory NN in SOH estimation of lithium-ion batteries has received wide attention.Reports so far have shown that the utilization of NN to model the SOH of lithium-ion batteries has the advantages of high efficiency,low energy consumption,high robustness,and scalable models.In the future,NN can make a greater contribution to lithium-ion battery management by,first,utilizing more field data to play a more practical role in health feature screening and model building,and second,by enhancing the intelligent screening and combination of battery parameters to characterize the actual lithium-ion battery SOH to a greater extent.The in-depth application of NN in lithium-ion battery SOH will certainly further enhance the science,reliability,stability,and robustness of lithium-ion battery management.