Electric Vehicle Power Battery Research Articles

A Shared Charging Channel for Power and Auxiliary Batteries in Electric Vehicles

A Shared Charging Channel for Power and Auxiliary Batteries in Electric Vehicles

Development of a cooling system for marine power batteries

For green shipping, lithium-ion battery-powered ships are rapidly developing. Compared with power batteries for electric vehicles, the large volume and capacity of cells in electric ships make it difficult to dissipate heat, thus requiring efficient cooling. Herein, a novel shape-stabilized phase change material (SSPCM) channel/thermoelectric cooler (TEC) cooling system for marine power batteries was proposed and experimentally studied. It uses TEC for localized cooling and seawater flowing inside the SSPCM as coolant. First, the arrangement of the TECs was experimentally determined. Then, the cooling performance of the system was verified by comparative experiments. The results show that, compared to the cooling system without TECs, the maximum temperature difference was reduced by 28.8 %, with the maximum temperature and temperature difference of 49.8 °C and 3.7 °C, respectively. Compared with the single cooling method, the maximum temperature and temperature difference were reduced by 15.5 % and 53.3 %, respectively. Finally, the experiments were conducted to explore the impact of various parameters on the cooling performance of the system. The unique combination of SSPCM channel, seawater, and TEC provides a new strategy for efficiently cooling marine power batteries at high charge/discharge rates.

METHODOLOGY FOR EXPERIMENTAL RESEARCH OF THE FIRE HAZARD OF POWER LITHIUM-ION BATTERIES OF ELECTRIC VEHICLES UNDER THE INFLUENCE OF A HEATING PANEL

Even though lithium-ion batteries (LIBs) are the subject of various tests and research at the production stage, there are no isolated cases of electric vehicle fires, and the development dynamics are unpredictable. The particular danger of such fires lies in the oxygen release during an irreversible exothermic reaction in LIBs, which creates new challenges for fire and rescue services when extinguishing such fires. The study aims to develop the main provisions of the methodology for experimental studies of electric vehicle power batteries in terms of fire hazards using an electric heating panel. The ultimate goal of the study is to determine the temperatures at which an irreversible exothermic reaction, the opening of ventilation holes, and the combustion (explosion) of electric vehicle power batteries begin, as well as the time parameters at which such processes occur. Taking into account the peculiarities of the occurrence and course of the irreversible exothermic reaction, we have developed a methodology, the essence of which is to determine the temperatures of the onset of the irreversible exothermic reaction of the electric vehicle power battery, the opening of ventilation holes, and the combustion (explosion) of electric vehicle power batteries, the combustion temperatures of ventilation gases, as well as the time parameters at which these processes occur, which may change during battery operation and not correspond to the declared parameters of the manufacturer. For this purpose, we exposed LIBs to thermal energy from an electric heating panel and recorded the temperature and time during which an irreversible exothermic reaction occurs from the moment of an internal short circuit to a fire or explosion. The use of the proposed methodology of experimental studies of the elements of power batteries of electric vehicles regarding the fire hazard of an electric heating panel will make it possible to determine the temperature limits of the occurrence of irreversible exothermic reactions in LIBs, as well as the time parameters under which these processes occur. Keywords: electric vehicle fire, irreversible exothermic reaction, lithium-ion battery.

High-Frequency AC Heating Strategy of Electric Vehicle Power Battery Pack in Low-Temperature Environment.

In this paper, a heating strategy using high-frequency alternating current (AC) is proposed to internally heat lithium-ion batteries (LIB) at low temperatures. The strategy aims to strike a good balance between rapid heating of the battery at low temperatures and minimizing damage to the battery's lifespan without the need for an additional power source. The strategy presents an electrochemical-thermal coupling model to simulate and predict the temperature rise and temperature distribution of a 50 A h LiFePO4 square battery at different C-rates, the effect of high-frequency AC on battery life, and the validity of the model as verified by experiments. The experimental and simulation results show that this strategy can achieve faster heating speeds and better temperature consistency without affecting battery life. The best heating effect can be achieved at a frequency of 500 Hz (4.2C), and the temperature of the battery rises from 253.15 to 278.15 K within 365 s, for an average heating rate of 3.29 K/min. Researching low-temperature AC heating methods has important value for energy conservation because it can improve heating efficiency, expand application areas, promote technological innovation, and enhance product quality.

Multi-Fault Diagnosis of Electric Vehicle Power Battery Based on Double Fault Window Location and Fast Classification

As energy supply units, lithium-ion batteries have been widely used in the electric vehicle industry. However, the safety of lithium-ion batteries remains a significant factor limiting their development. To achieve rapid fault diagnosis of lithium-ion batteries, this paper presents a comprehensive fault diagnosis process. Firstly, an interleaved voltage sensor topology structure is utilized to acquire battery voltage data. An improved complete ensemble empirical mode decomposition with adaptive noise method is introduced to process data. Then, the reconstructed voltage data sequence is used to eliminate the influence of noise. A fault location is performed using dichotomy correlation coefficient and time window correlation coefficient. Afterwards, principal component analysis is used to select the principal components with high contribution rate as classification features. The gray wolf optimization algorithm is used to find the parameters of the least squares support vector machine, constructing an optimal classifier for fault classification. A fault experiment platform is established to realize the physical triggering of faults such as external short circuit, internal circuit, and connection of experimental battery packs. Finally, the accuracy and reliability of the method are verified by the results of fault localization and fault type determination.

Research on the interaction between energy consumption and power battery life during electric vehicle acceleration

Most studies on the acceleration process of electric vehicle focus on reducing energy consumption, but do not consider the impact of the power battery discharge current and its change rate on the battery life. Therefore, this paper studied the interaction between electric vehicle energy consumption and power battery capacity attenuation during acceleration. First, a power battery life model for electric vehicle under driving conditions is established, and the percentage of battery capacity loss per kilometer is used to measure the capacity loss under different acceleration conditions. Then, the relationship between the percentage of battery capacity loss per kilometer and velocity and acceleration is explored, and the capacity attenuation mechanism of power battery under different acceleration processes is analyzed. Finally, the energy consumption and battery capacity attenuation is studied when the electric vehicle accelerated with multiple accelerations curves, and the interaction of the first acceleration and acceleration time on the electric vehicle energy consumption and the power battery capacity attenuation characteristics is discussed. The research results indicate that when the electric vehicle accelerates with different multiple accelerations curves, the change of energy consumption per kilometer and percentage of battery capacity loss per kilometer with acceleration and acceleration time is different, and the change of the two is basically opposite.

Energy Efficiency Analysis and Research of Pure Electric Vehicles under Actual Working Conditions

Pure electric vehicles are a hot topic in today’s social development. From beginning to end, the energy density of power batteries in pure electric vehicles is generally low, resulting in short range, inaccurate range estimation, and driver anxiety. This is also one of the reasons that hinder the promotion of pure electric vehicles. This article discusses the energy consumption of pure electric vehicles based on actual road tests. By comparing the battery energy efficiency of various roads (including urban roads, suburban roads, and highways) using electric vehicles from Guangzhou to Qingyuan, the energy consumption patterns of pure electric vehicles are analyzed. Experiments have shown that continuously improving the energy density of power batteries is the key technology to solve the problem of insufficient range for electric vehicles. Based on the existing power battery technology, this study investigates the relationship between energy consumption and various factors affecting electric vehicles, which can provide better reference for drivers to predict energy consumption and range.

Research on Adaptability of Temperature Characteristic for Electric Vehicle Power Battery

The operating temperature of power lithium-ion batteries in different application scenarios and working conditions not only relates to the economic cost and power performance of the energy system, but also directly affects its life. Therefore, based on the vehicle-mounted power battery, a comprehensive battery test platform was built to carry out charge and discharge tests, and the relationship between capacity and temperature was studied. In the temperature range of -30~50℃, a temperature gradient of 20℃ was used to obtain the charge/discharge curves at different temperatures, and the temperature characteristics of the power LFP batteries were analyzed in terms of charging and discharging.Based on data analysis, the conclusions of the study provide numerical references for the control of temperature thresholds for power battery applications.

Experimental study of thermal runaway propagation suppression of lithium-ion battery module in electric vehicle power packs

In this study, the thermal runaway (TR) suppression test platform of battery modules was built based on the real power battery pack to reduce the thermal runaway propagation (TRP) of electric vehicle power battery packs. The inhibition effect of different fire extinguishing devices on TRP of ternary lithium-ion battery modules was experimentally investigated. Big scale tests yielded combustion behaviors, TRP intervals, peak temperatures, cooling efficacy of extinguishants, heat transfer, and fire traces of the battery modules. Notably, perfluorohexanone application prolonged the TRP by 427 s relative to the blank control experiment, reducing the cell casing temperature to 267 ℃, although it did not fully arrest TRP between cells. However, water mist application effectively halted inter-cell TRP, ensuring post-spray temperatures at thermocouple sites remained below 100 ℃ and reduced heat transfer best. These findings deliver crucial experimental insights that bolster the development of fire extinguishing strategies for the safety management of electric vehicle power battery assemblies.

Powertrain structure analysis of extended range electric vehicles

Since its invention, the internal combustion engine has greatly contributed to the development of human civilization and is also an important symbol of the progress of human civilization. The energy and environmental problems brought by traditional automobiles have seriously restricted the development of today's automotive industry. Due to the bottleneck of pure electric vehicle power battery technology, its short range and short battery life, the extended range electric vehicle is a smooth transition model of the pure electric vehicle, with its high efficiency, small battery capacity, long driving range and other advantages have received widespread attention. In this paper, the key technical issues, including the component selection, parameter matching, and control strategy of the extended-range electric vehicle drive system, are analyzed and discussed in detail. Several issues worthy of attention in future research are pointed out in the paper and provide insights for further development of extended-range electric vehicles.

Indium doping: An effective route to optimize the electrochemical performance of LiFePO4 cathode material

This study aimed to develop In-doped LiFePO4 cathode materials for lithium ion power batteries in electric vehicles that meet the requirements of both fast acceleration and long-term reversible charge-discharge stability. We focused on investigating the role of indium doping in enhancing high-rate capability. Density functional theory (DFT) calculations revealed that successful substitution of In at Fe site exhibits distinct features for both LiFe1-xInxPO4 and Fe1-xInxPO4. The results showed that the presence of In in unlithiated Fe1-xInxPO4 can lower the diffusion energy barrier of lithium ions. On the other hand, the introduction of In in lithiated LiFe1-xInxPO4 creates an impurity energy band at the Fermi energy level, which enhances electron conductivity of the active material. Experimental data demonstrated that with 2% In doping, the 2% In3+-LFP/C electrode delivers 160 mAh g−1 at 0.1C, and 150 mAh g−1 at 1C (with excellent retention rate of 98% after 700 cycles). Additionally, the In-doped electrode provided higher discharge capacity at high-rates (5C and 10C) due to improved electron conductivity and lithium ion diffusion properties. These findings prove that indium doping is an effective approach to reinforcing the electrochemical capabilities of high-rate LiFePO4 cathode material for lithium storage.

State of health estimation and prediction of electric vehicle power battery based on operational vehicle data

State of health estimation and prediction of electric vehicle power battery based on operational vehicle data

Finite element modeling of electric vehicle power battery pack and its influence analysis and test research at body-in-white stage

Compared with the design of traditional fuel vehicles, the design of electric vehicles has its uniqueness, consisting mainly in that the body design must be able to adapt to the new power system and its layout. Power battery pack is an important factor affecting the body design of electric vehicles. In order to study the modeling of power battery packs and its impact on body performance, it was proposed to use the finite element method for modeling the power battery pack and analyzing its influence on the performance of the body-in-white. Based on a certain electric vehicle, the basic body-in-white model and the body-in-white model with the mass point addition and the refined model of the power battery pack were established, the static stiffness of the body-in-white simulation results of different models were compared and analyzed, and finally the effectiveness of the simulation model was verified through bench tests. Based on this effective model, the influence of the power battery pack on the modal and strength of the body-in-white was analyzed. The results show that the established refined model of the power battery pack has higher computational accuracy. Besides, the power battery pack can significantly increase the static stiffness of the electric vehicle body-in-white, effectively optimize the first-order torsion frequency and the first-order front cabin yaw frequency of the body-in-white, reduce the first-order bending frequency of the body-in-white, and greatly increase the risk of static strength failure of the body-in-white. In the setting of body performance goals and structural development, the influence of the power battery pack cannot be ignored.

Research on SOC estimation method of hybrid electric vehicles battery based on the grey wolf optimized particle filter

In this paper, we propose a method called grey wolf optimized particle filter (GWO-PF) to estimate the state of charge (SOC) of the power battery in hybrid electric vehicles (HEVs). The GWO-PF method combines the particle distribution mechanism with grey wolf optimization to achieve accurate SOC estimation. To begin, we compare four different equivalent circuit models of power batteries and select the second-order RC model (RC2 model) as our research focus. Next, we identify the parameters of the RC2 model online using the recursive least square method with a forgetting factor. Finally, we utilize the identified parameters to implement the GWO-PF method for SOC estimation. We compare the performance of the GWO-PF method with two other commonly used methods: the unscented Kalman filter (UKF) and the particle filter (PF). The results demonstrate that the GWO-PF method achieves high precision in SOC estimation, with a controllable relative error within 3.5%.

Retracted: Research on the Early Warning Mechanism for Thermal Runaway of Lithium-Ion Power Batteries in Electric Vehicles

Retracted: Research on the Early Warning Mechanism for Thermal Runaway of Lithium-Ion Power Batteries in Electric Vehicles

Evaluation of the safety standards system of power batteries for electric vehicles in China

In recent years, electric vehicle safety incidents related to batteries have occurred frequently enough to question the adequacy of the current international safety standards. As the world's leading producer of batteries for electric vehicles, China has thus formulated its own national standards, but there are questions as to the unique value of these standards. This review paper analyzes the Chinese safety standards from the perspective of the battery materials, cells, modules, battery systems, battery management systems, and vehicles. The findings from the analysis of the Chinese standards is used to provide suggestions for building better international battery safety standards with recommendations for different battery levels, battery life cycle design and emerging battery technologies.

Piranha Solution-Assisted Surface Engineering Enables Silicon Nanocrystals with Superior Wettability and Lithium Storage

Silicon anodes with a high theoretical capacity possess great potential applications in power batteries for electric vehicles, while their volume expansion always leads to crystal pulverization and electrode polarization. An ideal solution to alleviate such pulverization and polarization of silicon crystals is to simultaneously use nano-sized silicon crystals and introduce high viscosity and elasticity polymer binders. This work has achieved the adjustable introduction of hydroxyl groups to silicon nanocrystals under the optimal reaction temperature (e.g., 80 °C) and appropriate piranha solution composition (e.g., H2SO4/H2O2 = 3:1 v/v), ultimately forming an amorphous coating layer of ~1.3 nm on the silicon surface. The optimized silicon anode exhibits superior electrochemical performance (with an initial Coulombic efficiency of 85.5%; 1121.4 mA h g−1 at 1 A g−1 after 200 cycles) and improved hydrophilicity. The introduced hydroxyl groups significantly enhance the hydrophilicity of silicon in the electrolyte and the electrochemical activity of the silicon anodes. The hydroxyl groups achieve stronger bonding between silicon and polymer binders, ultimately improving the mechanical strength and stability of the electrode. The introduction of hydrophily functional groups on the surface of silicon crystals can be explored as an active strategy to solve the above issues. This surface engineering method could be extended to more fields of infiltrating silicon-based functional materials.

Study on the Integration Strategy of Online EOL Testing of Pure Electric Vehicle Power Battery.

This paper analyzes the electrical test items of the EOL testing line in automotive manufacturers. On this basis, this paper proposes and designs an integrated and automated testing strategy to deal with the problems of slow testing speed, high dependence on manual labor and low efficiency. This article mainly analyzes the various tests of the two main tests in battery EOL testing: Battery Management System (BMS) testing and electrical testing. We propose an innovative integrated solution based on various testing items, including the reception, transmission, and self-analysis of different UDS protocol messages, a unique automated electrical performance measurement scheme, and a requirement and logic design of an integrated software end based on Python. The experimental results of actual testing show that the implementation of the integrated strategy greatly reduces the complexity of the testing steps, improves the testing efficiency, and reduces errors caused by human operation.

Adaptive Optimal Control of Hybrid Electric Vehicle Power Battery via Policy Learning.

An online policy learning algorithm is used to solve the optimal control problem of the power battery state of charge (SOC) observer for the first time. The design of adaptive neural network (NN) optimal control is studied for the nonlinear power battery system based on a second-order (RC) equivalent circuit model. First, the unknown uncertainties of the system are approximated by NN, and a time-varying gain nonlinear state observer is designed to address the problem that the resistance capacitance voltage and SOC of the battery cannot be measured. Then, to realize the optimal control, a policy learning-based online algorithm is designed, where only the critic NN is required and the actor NN widely used in most design of the optimal control methods is removed. Finally, the effectiveness of the optimal control theory is verified by simulation.

Novel approach for liquid-heating lithium-ion battery pack to shorten low temperature charge time

The charging time for Li-ion power battery in hybrid electric vehicles (HEVs) and pure electric vehicles (EVs) is elongated at low temperature compared to that at the room temperature, which will deteriorate the customer using experience. Therefore, shortening the low-temperature charging time of battery is the critical technology to promote the popularization of electric vehicles. Many techniques have been proposed to shorten the low-temperature charging time, but these technologies often lead to problems such as the increase of vehicle energy consumption, the high temperature of the battery pack system (BPS) at the end of charging and the poor BPS temperature uniformity during charging. To tackle these problems, this paper proposes an optimization simulation model for charging control strategy combined with thermal model (SCCS-ThM) and BPS offline parameters based on a liquid heating thermal management system (LHTMS). The BPS offline parameters determine the charging power threshold under different ambient temperature and the different state of capacity (SoC). The temperature rise and the temperature differences of the BPS during charging are calculated with the thermal model. The optimization model obtains the optimal charging strategy by simulating the potential feasible charging strategies. The battery pack charge time is reduced by introducing a pre-heating stage prior to charging. The pre-heating period which minimizes overall charge time, including the pre-heating time, is determined using the thermal model. The experimental results show that for an initial battery pack temperature of −10 °C, overall charge time is minimized by starting to charge after the battery pack has been heated to 1 °C. With the same charging energy, the optimal charging strategy shortens the charging time by 16 % and reduces battery coolant heater energy consumption by 15 %. Besides, the maximum temperature at the end of charging and the maximum temperature difference during the whole charging process are 36 °C and 6 °C respectively, which are better than the original charging strategy.