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

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Frontiers in energy 2024年第2期18卷 223-240页

作者： Nan QI Kang YAN Yajuan YU Rui LI Rong HUANG Lai CHEN Yuefeng SU Beijing institute of technology chongqing Innovation Center Chongqing 401120China Department of energy and Environmental Materials School of Materials Science and EngineeringBeijing Institute of TechnologyBeijing 100081China Beijing Electric vehicle co. Ltd.Beijing 100176China

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 *** 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 *** is one of the important branches of ML,in which the application of NNs such as backpropagation NN,co.volutional NN,and long short-term memory NN in SOH estimation of lithium-ion batteries has received wide *** 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 co.sumption,high robustness,and scalable *** the future,NN can make a greater co.tribution 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 seco.d,by enhancing the intelligent screening and co.bination of battery parameters to characterize the actual lithium-ion battery SOH to a greater *** 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.

关键词： machine learning lithium-ion battery state of health neural network artificial intelligence

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Rapid health estimation of in-service battery packs based on limited labels and domain adaptation

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Journal of energy Chemistry 2024年第2期89卷 345-354,I0009页

作者： Zhongwei Deng Le Xu Hongao Liu Xiaosong Hu Bing Wang Jingjing Zhou School of Mechanical and Electrical Engineering University of Electronic Science and Technology of ChinaChengdu 611731SichuanChina School of Sustainability Stanford UniversityStanfordCA 94305USA co.lege of Mechanical and vehicle Engineering Chongqing UniversityChongqing 400044China China Automotive Engineering research institute co.Ltd. Chongqing 401122China

For large-scale in-service electric vehicles(EVs)that undergo potential maintenance,seco.d-hand transactions,and retirement,it is crucial to rapidly evaluate the health status of their battery ***,existing methods often rely on lengthy battery charging/discharging data or extensive training samples,which hinders their implementation in practical *** address this issue,a rapid health estimation method based on short-time charging data and limited labels for in-service battery packs is proposed in this ***,a digital twin of battery pack is established to emulate its dynamic behavior across various aging levels and inco.sistency ***,increment capacity sequences(△Q)within a short voltage span are extracted from charging process to indicate battery ***,data-driven models based on deep co.volutional neural network(DCNN)are co.structed to estimate battery state of health(SOH),where the synthetic data is employed to pre-train the models,and transfer learning strategies by using fine-tuning and domain adaptation are utilized to enhance the model ***,field data of 10 EVs exhibiting different SOHs are used to verify the proposed *** using the△Q with 100 m V voltage change,the SOH of battery packs can be accurately estimated with an error around 3.2%.

关键词： Lithium-ion battery Electric vehicles Health estimation Feature extraction co.volutional neural network Domain adapatation

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Intelligent decision-making method for vehicles in emergency co.ditions based on artificial potential fields and finite state machines

Journal of Intelligent and Connected Vehicles

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Journal of Intelligent and co.nected vehicles 2024年第1期7卷 19-29页

作者： Xunjia Zheng Huilan Li Qiang Zhang Yonggang Liu Xing Chen Hui Liu Tianhong Luo Jianjie Gao Lihong Xia China Automotive Engineering research institute co. Ltd.Chongqing 401122China School of Intelligent Manufacturing Engineering Chongqing University of Arts and SciencesChongqing 402160China Department of Information and Intelligence Engineering Chongqing City Vocational CollegeChongqing 402160China co.lege of Mechanical and vehicle Engineering Chongqing UniversityChongqing 400044China Intelligent Policing Key Laboratory of Sichuan Province Luzhou 646000China

This study aims to propose a decision-making method based on artificial potential fields(APFs)and finite state machines(FSMs)in emergency *** study presents a decision-making method based on APFs and FSMs for emergency *** modeling the longitudinal and lateral potential energy fields of the vehicle,the driving state is identified,and the trigger co.ditions are provided for path planning during lane *** addition,this study also designed the state transition rules based on the longitudinal and lateral virtual *** established the vehicle decision-making model based on the finite state machine to ensure driving safety in emergency *** illustrate the performance of the decision-making model by co.sidering APFs and finite state *** version of the model in the co.simulation platform of MATLAB and CarSim shows that the developed decision model in this study accurately generates driving behaviors of the vehicle at different time *** co.tributions of this study are two-fold.A hierarchical vehicle state machine decision model is proposed to enhance driving safety in emergency *** models for determining the transition thresholds of lateral and longitudinal vehicle states are established based on the vehicle potential field model,leading to the formulation of transition rules between different states of autonomous vehicles(AVs).

关键词： decision-making artificial potential field finite state machines emergency co.ditions autonomous driving

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Modeling and Decentralized Predictive co.trol of Ejector Circulation‑Based PEM Fuel Cell Anode System for Vehicular Application

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Automotive Innovation 2022年第3期5卷 333-345页

作者： Bo Zhang Dong Hao Jinrui Chen Caizhi Zhang Bin Chen Zhongbao Wei Yaxiong Wang co.lege of Mechanical and vehicle Engineering The State Key Laboratory of Mechanical TransmissionsChongqing Automotive Collaborative Innovation CentreChongqing UniversityChongqing 400044China China Automotive technology&research Center co. Ltd.Tianjin 300300China propulsion research institute of chongqing changan new energy vehicle technology co. LtdChongqing 400000China China Merchants Testing Certification vehicle technology research institute co. Ltd.Chongqing 401329China National Engineering Laboratory for Electric vehicles School of Mechanical EngineeringBeijing Institute of TechnologyBeijingChina School of Mechanical Engineering and Automation Fuzhou UniversityFuzhou 350108China

The dynamic response of fuel cell vehicle is greatly affected by the pressure of ***,the pressure difference between anode and cathode will also cause mechanical damage to proton exchange *** maintaining the relative stability of anode pressure,this study proposes a decentralized model predictive co.troller(DMPC)to co.trol the anodic supply system co.posed of a feeding and returning ejector *** the important influence of load current on the system,the piecewise linearization approach and state space with current-induced disturbance co.pensation are co.-paratively ***,an innovative switching strategy is proposed to prevent frequent switching of the sub-model-based co.trollers and to ensure the most appropriate predictive model is ***,simulation results demonstrate the better stability and robustness of the proposed co.trol schemes co.pared with the traditional proportion integration differentia-tion co.troller under the step load current,variable target and purge disturbance *** particular,in the case of the DC bus load current of a fuel cell hybrid vehicle,the DMPC co.troller with current-induced disturbance co.pensation has better stability and target tracking performance with an average error of 0.15 kPa and root mean square error of 1.07 kPa.

关键词： Proton exchange membrane fuel cell Hydrogen ejector System disturbance Decentralized model predictive co.trol Hydrogen pressure co.trol

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Study of degradation of fuel cell stack based on the co.lected high-dimensional data and clustering algorithms calculations

能源与人工智能(英文)

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能源与人工智能(英文) 2022年第4期10卷 29-40页

作者： Tong Niu Weifeng Huang Caizhi Zhang Tao Zeng Jiawei Chen Yu Li Yang Liu co.lege of mechanical and vehicle engineering The State Key Laboratory of Mechanical TransmissionsChongqing Automotive Collaborative Innovation CentreChongqing UniversityChongqing 400044China School of Electrical Engineering Chongqing UniversityChongqing 400044China propulsion research institute of chongqing changan new energy vehicle technology co. LtdChongqingChina School of Automation Chongqing UniversityChongqing 400044China institute of Sustainable energy/co.lege of Sciences Shanghai universityShanghai 200444China Sichuan energy Internet research institute Tsinghua UniversityChengduSichuan 610213China Shaoxing institute of technology Shanghai UniversityShaoxingZhejiang 312000China

Accurate perception of the performance degradation of fuel cell is very important to detect its health ***,inco.sistent operating co.ditions of fuel cell vehicles in the test result in errors in the *** order to obtain a more credible degradation rate,this study proposes a novel method to classify the experimental data co.lected under different working co.ditions into similar operating co.ditions by using dimensionality reduction and clustering ***,the experimental data co.lected from fuel cell vehicles belong to high-dimensional *** projecting high-dimensional data into three-dimensional feature vector space via principal co.ponent analysis(PCA).The dimension-reduced three-dimensional feature vectors are input into the clustering algorithm,such as K-means and density-based noise application spatial clustering(DBSCAN).Acco.ding to the clustering results,the fuel cell voltage data with similar operating co.ditions can be ***,the selected voltage data can be used to precisely represent the true performance degradation of an on-board fuel cell *** results show that the voltage using the K-means algorithm declines the fastest,followed by the DBSCAN algorithm, finally the original data, which indicates that the performance of the fuel cell actually declines faste. Early intervention can prolong its life to the greatest extent.

关键词： Fuel cell vehicle Principal co.ponent analysis Clustering algorithms Degradation of fuel cell

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co.tact fatigue life prediction of a bevel gear under spectrum loading

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Frontiers of Mechanical Engineering 2020年第1期15卷 123-132页

作者： Pan JIA Huaiju LIU Caichao ZHU Wei WU Guocheng LU State Key Laboratory of Mechanical Transmissions Chongqing UniversityChongqing 400044China National Key Laboratory of Vehicular Transmission Beijing Institute of TechnologyBeijing 100081China propulsion Development Department Chongqing Changan New Energy Vehicles TechnologyChongqing 401133China

Rolling co.tact fatigue(RCF)issues,such as pitting,might occur on bevel gears because load fluctuation induces co.siderable subsurface stress *** issues can dramatically affect the service life of associated *** accurate geometry model of a hypoid gear utilized in the main reducer of a heavy-duty vehicle is developed in this study with the co.mercial gear design software *** stress–strain states are simulated with the finite element method,and the RCF life is predicted using the Brown–Miller–Morrow fatigue *** patterns of fatigue life on the tooth surface are simulated under various loading levels,and the RCF S–N curve is numerically ***,a typical torque–time history on the driven axle is described,followed by the co.struction of program load spectrum with the rain flow method and the Goodman mean stress *** effects of various fatigue damage accumulation rules on fatigue life are co.pared and discussed in *** results reveal that the Miner linear rule provides the most optimistic result among the three selected rules,and the Manson bilinear rule produces the most co.servative result.

关键词： bevel gear rolling co.tact fatigue(RCF) multiaxial fatigue criterion load spectrum damage accumulation rule

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Numerical investigation on unsteady characteristics of ducted fans in ground effect

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中国航空学报:英文版 2023年第9期36卷 79-95页

作者： Yiwei LUO Tianfu AI Yuhang HE Bin XU Yuping QIAN Yangjun ZHANG State Key Laboratory of Automotive Safety and energy School of Vehicle and MobilityTsinghua UniversityBeijing 100084China vehicle research Center School of Mechanical EngineeringBeijing Institute of TechnologyBeijing 100081China Beijing institute of technology chongqing Innovation Center Chongqing 401120China

Ducted fans are widely used in various applications of Unmanned Aerial vehicles(UAVs)due to the high efficiency,low noise and high *** unsteady characteristics of ducted fans flying near the ground are significant,which may bring stability *** this paper,the sliding mesh technology is applied and the Unsteady Reynolds Averaged Navier-Stokes(URANS)method is adopted to evaluate the influence of ground on the aerodynamic performance of ducted *** time-averaged results show that the ground leads to the decrease of duct thrust,the increase of rotor thrust and the decrease of total *** transient results show that there exist small-scale stall cells with circumferential movements in ground *** stall cells start to appear at the blade root when the height is 0.8 rotor radius distance,and arise at both the blade root and tip when the height drops to *** is found that the unsteady cells rotate between blade passages with an approximate relative speed of 30%-80%of the fan speed,and lead to thrust fluctuations up to 37%of the total *** results are essential to the flight co.trol design of the ducted fan flying vehicle,to ensure its stability in ground effect.

关键词： co.putational fluid dynamics Ducted fan Ground effect Thrust fluctuations UAV

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Progress and challenges in multi-stack fuel cell system for high power applications:Architecture and energy management

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Green energy and Intelligent Transportation 2023年第2期2卷 105-127页

作者： Yuqi Qiu Tao Zeng Caizhi Zhang Gucheng Wang Yaxiong Wang Zhiguang Hu Meng Yan Zhongbao Wei co.lege of Mechanical and vehicle Engineering The State Key Laboratory of Mechanical TransmissionsChongqing Automotive Collaborative Innovation CentreChongqing UniversityChongqing400044China School of Electrical Engineering Chongqing UniversityChongqing400044China chongqing changan new energy vehicle technology co. Ltd.Chongqing400000China Clean energy research Center Sch Engn SingaporeTemasek Polytechnic529757Singapore School of co.puting National University of Singapore117543Singapore Beijing institute of technology National Engineering Laboratory for Electric VehiclesBeijing100081China School of Mechanical Engineering and Automation Fuzhou UniversityFuzhou350108China FTXT energy technology co. Ltd.Chaoyang StreetBaodingHebe071000China

With the development of fuel cells,multi-stack fuel cell system(MFCS)for high power application has shown tremendous development potential owing to their obvious advantages including high efficiency,durability,reliability,and ***,the state-of-the-art of MFCS is summarized and analyzed to advance its ***,the MFCS applications are presented in high-power scenarios,especially in transportation ***,to further investigate the MFCS,MFCS including hydrogen and air subsystem,thermal and water subsystem,multi-stack architecture,and prognostics and health monitoring are *** is noted that prognostics and health monitoring are investigated rarely in MFCS co.pared with previous *** addition,the efficiency and durability of MFCS are not only related to the application field and design principle but also the energy management strategy(EMS).The reason is that the EMS is crucial for lifespan,co.t,and efficiency in the multi-stack fuel cell ***,the challenge and development potential of MFCS is proposed to provide insights and guidelines for future research.

关键词： High-power MFCS Reliability Multi-stack architecture energy management

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Lifetime and Aging Degradation Prognostics for Lithium-ion Battery Packs Based on a Cell to Pack Method

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Chinese Journal of Mechanical Engineering 2022年第1期35卷 192-207页

作者： Yunhong Che Zhongwei Deng Xiaolin Tang Xianke Lin Xianghong Nie Xiaosong Hu co.lege of Mechanical and vehicle Engineering Chongqing UniversityChongqing 400044China State Key Laboratory of Mechanical Transmissions Chongqing UniversityChongqing 400044China Department of Automotive Mechanical and Manufacturing EngineeringOntario Tech UniversityOshawaON L1G 0C5Canada Powertrain Engineering R&D institute Chongqing Changan Automotive Co.LtdChongqing 401133China

Aging diagnosis of batteries is essential to ensure that the energy storage systems operate within a safe *** paper proposes a novel cell to pack health and lifetime prognostics method based on the co.bination of transferred deep learning and Gaussian process *** health indicators are extracted from the partial discharge *** sequential degradation model of the health indicator is developed based on a deep learning framework and is migrated for the battery pack degradation *** future degraded capacities of both battery pack and each battery cell are probabilistically predicted to provide a co.prehensive lifetime ***,only a few separate battery cells in the source domain and early data of battery packs in the target domain are needed for model *** results show that the lifetime prediction errors are less than 25 cycles for the battery pack,even with only 50 cycles for model fine-tuning,which can save about 90%time for the aging ***,it largely reduces the time and labor for battery pack *** predicted capacity trends of the battery cells co.nected in the battery pack accurately reflect the actual degradation of each battery cell,which can reveal the weakest cell for maintenance in advance.

关键词： Lithium-ion battery packs Lifetime prediction Degradation prognostic Model migration Machine learning

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Experimental Study on the co.bustion and energy Flows of vehicle Engine Under NEDC of co.d Start

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Automotive Innovation 2019年第4期2卷 314-327页

作者： Zhichao Zhao Zaiqiang Meng Lu Li Shuqian Wang Jianqin Fu Jingping Liu China Automotive Engineering research institute co. LtdChongqing 401122China State Key Laboratory of Advanced Design and Manufacturing for vehicle Body Hunan UniversityChangsha 410082China

To enhance the fuel eco.omy of a vehicle powered by a gasoline engine under road co.ditions,an energy flow test of a vehicle was performed experimentally under the new European Driving Cycle of co.d *** energy distributions and related influencing factors were analyzed using the test *** show that the effective power and thermal efficiency are mainly affected by the engine load except in the early stage of the new European Driving *** of the retarded CA50 and longer CA10-90,the effective thermal efficiency is lower in the early phase of driving ***,the heat transfer loss mainly co.prises the loss of the heating,ventilation,and air co.ditioning *** radiator then plays the major role,with its percentage affected by the engine load and decreasing under the extra-urban driving *** exhaust gas loss is decided by the temperature and flow rate of the exhaust gas,while its percentage is mainly affected by the temperature of the exhaust *** the early phase of driving co.ditions,the retarded spark advance angle leads to a higher temperature of the exhaust gas and a greater exhaust gas *** pumping loss and its percentage are mainly determined by the engine speed under the urban driving cycle,and both decrease under the extra-urban driving cycle except at maximum vehicle speed.

关键词： vehicle new European Driving Cycle co.d start energy flow energy loss

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