ENHANCING NEW ENERGY VEHICLE RELIABILITY: ELECTRONIC DIAGNOSIS
The emergence of new energy vehicles (NEVs) has revolutionized the transportation sector by offering a sustainable and environmentally friendly alternative to traditional fuel-driven vehicles. Entropy-based voltage fault diagnosis of battery systems for electric vehicles. Energies, 11(1), 136. Hu, X., Zhang, K., Liu, K., Lin, X., Dey, S
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087-104 2020-0757 孙振宇
Overview of Fault Diagnosis in New Energy Vehicle Power Battery System SUN Zhenyu 1, 2 WANG Zhenpo 1, 2, 3 LIU Peng 1, 2, 3 ZHANG Zhaosheng 1, 2, 3 CHEN Yong 4 QU Changhui 1, 2
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Research progress, challenges and prospects of fault diagnosis
This paper discusses the research progress of battery system faults and diagnosis from sensors, battery and components, and actuators: (1) the causes and influences of sensor fault, actuator fault, internal/external short circuit fault, overcharge/over-discharge fault, connection fault, inconsistency, insulation fault, thermal management system
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A Review on the Fault and Defect
The battery system, as the core energy storage device of new energy vehicles, faces increasing safety issues and threats. An accurate and robust fault diagnosis technique is
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Prediction and Diagnosis of Electric Vehicle
Battery voltage is a pivotal parameter for evaluating battery health and safety. The precise prediction of battery voltage and the implementation of anomaly detection
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Fault diagnosis technology overview for lithium‐ion battery energy
For the overcharge fault, the authors in ref. conduct several overcharge experiments, then analysed in detail the fault characteristics and the fault mechanism, and proposed a fault diagnosis method based on the voltage curve. Specifically, 11 overcharge cycles of 105% SOC were conducted on a LiFePO4 cell (Rated capacity: 40 Ah, rated internal
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Fault Diagnosis of Lithium-Ion Batteries Based on the Historical
In recent years, the number of safety accidents in new-energy electric vehicles due to lithium-ion battery failures has been increasing, and the lithium-ion battery fault diagnosis technology is particularly important to ensure the safe operation of electric vehicles. This paper proposes a method for lithium-ion battery fault diagnosis based on the historical trajectory of
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A New Method of Lithium Battery Insulation Fault Diagnosis
Xiong R, Sun W, Yu Q et al (2020) Research progress, challenges and prospects of fault diagnosis on battery system of electric vehicles. Appl Energy 279:115855. Article Google Scholar Wang Y, Tian J, Chen Z et al (2019) Model based insulation fault diagnosis for lithium-ion battery pack in electric vehicles.
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A fault diagnosis method for electric vehicle power lithium battery
With the increasingly serious energy and environmental problems, new energy vehicles are gaining widespread attention and development worldwide [1].Lithium-ion battery system has become the main choice of power source for new energy vehicles because of its advantages of high power density, high energy density and long cycle life [2].However, with
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Battery leakage fault diagnosis based on multi-modality multi
With the rapid development of the new energy vehicle industry and the overall number of electric vehicles, the thermal runaway problem of lithium-ion batteries has become a major obstacle to the promotion of electric vehicles. Therefore, the study of battery fault diagnosis technology and the realization of early warning has become a
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Autoencoder-Enhanced Regularized Prototypical Network for New Energy
The new energy vehicle (NEV) battery fault detection problem is challenging because of the extreme class imbalance in the data collected, leading traditional neural network algorithms to favor normal classes with larger sample sizes and thus ignore faulty classes. Battery fault diagnosis for electric vehicles based on voltage abnormality by
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Overview of Fault Diagnosis in New Energy Vehicle Power Battery
Overview of Fault Diagnosis in New Energy Vehicle Power Battery System: Zhenyu Sun, Zhenpo Wang *, Peng Liu, Zhaosheng Zhang, Yong Chen, Changhui Qu Overview of Fault Diagnosis in New Energy Vehicle Power Battery System: Original language: Chinese (Traditional) Pages (from-to) 87-104: Number of pages: 18:
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Recent advances in model-based fault diagnosis for lithium-ion
Among these, fault diagnosis plays a pivotal role in preserving the health and reliability of battery systems [6] as even a minor fault could eventually lead severe damage to LIBs [7], [8]. Hence, developing advanced and intelligent fault diagnosis algorithms for early detection of battery faults has become a hot research topic.
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Fault diagnosis of lithium-ion battery sensors based on multi
The battery management system of new energy vehicles is very important for the safe and smooth operation of the vehicle, which can maintain and monitor the battery status in real time [1].Battery management system is the implementation of control strategies from the battery monomer to the battery system through the information collected by the sensors, and
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An exhaustive review of battery faults and diagnostic techniques
Various abusive behaviors and working conditions can lead to battery faults or thermal runaway, posing significant challenges to the safety, durability, and reliability of
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A Review on the Fault and Defect Diagnosis
In this paper, the fault diagnosis of battery systems in new energy vehicles is reviewed in detail. Firstly, the common failures of lithium-ion batteries are classified, and the
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Data-Driven Fault Diagnosis Research and Software Development
With the goal of carbon neutrality, new energy power generation has been rapidly developed as a clean power generation technology [].The contradiction between the volatility of new energy and the security of the power grid is becoming increasingly prominent, and ESS plays an important role in promoting new energy consumption, stable operation
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Current Status and Innovative Research on Fault Diagnosis and
of the new energy automobile industry can be promoted [5]. 2. Common Fault Analysis of New Energy Vehicles . 2.1. Battery failure of new energy vehicles . The main new energy used by new energy vehicles refers to electrical energy, which is environmentally friendly. Due to its energysaving characteristics, it is deeply loved by automotive - users.
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Safety management system of new energy vehicle power battery
This algorithm is used for fault diagnosis in FDM and NEVPB to improve the safety of power batteries and ensure their normal operation. The proposed WOA-LSTM fault
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Fault diagnosis of new energy vehicles based on improved
The new energy vehicle system is in the initial stage of application, so the probability of fault is greater. Therefore, its reliability urgently needs to be improved. In order to improve the fault diagnosis effect of new energy vehicles, this paper proposes a fault diagnosis system of new energy vehicle electric drive system based on improved machine learning and
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Overview of Fault Diagnosis in New Energy Vehicle
In this paper, a simple and effective model-based sensor fault diagnosis scheme is developed to detect and isolate the fault of a current or voltage sensor for a series-connected lithium-ion...
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Fault and defect diagnosis of battery for electric vehicles based on
This paper presents a novel fault diagnosis method for battery systems in electric vehicles based on big data statistical methods. According to machine learning
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Battery voltage fault diagnosis mechanism of new energy vehicles
This work mainly discusses the establishment of the battery voltage fault diagnosis mechanism of new energy vehicles using electronic diagnosis technology. Based on electronic diagnosis
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Fault and defect diagnosis of battery for electric vehicles based on
Nowadays, scholars all over the world are studying the fault diagnosis of battery systems for improving the safety of EVs. For example, Chen et al. proposed a model-based fault diagnosis approach by investigating the external short circuit fault characteristics of lithium-ion batteries [9] y et al. proposed a two-state model for thermal fault diagnosis, which is able to
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Advancing fault diagnosis in next-generation smart battery with
This will significantly enhance fault diagnosis and warning capabilities of BMSs in terms of fast response times and low false alarm rates, fortifying the safety and reliability of
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Battery fault diagnosis and failure prognosis for electric vehicles
In application to battery fault diagnosis, for example, LSTM has demonstrated power in achieving accurate prediction of battery voltages with multiple inputs [43]. Moreover, the authors use LSTM to achieve synchronous multi-parameter prediction of battery systems, including voltage, temperature, and state of charge [ 44 ].
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Fault Diagnosis for Power Batteries Based
The power battery constitutes the fundamental component of new energy vehicles. Rapid and accurate fault diagnosis of power batteries can effectively improve the safety
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A method for battery fault diagnosis and
1 INTRODUCTION. Lithium-ion batteries are widely used as power sources for new energy vehicles due to their high energy density, high power density, and long
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Rapid diagnosis of power battery faults in new energy vehicles
fault identification of power battery failures in new energy vehicles. The second part introduces data preprocessing methods and proposes a fast diagnosis method for new energy vehicle power battery faults based on improved boosting algorithms and big data. The third part validates the effectiveness of the method. The fourth part discusses the
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(PDF) Optimized LSTM based on an improved sparrow search
Rapidly and accurately diagnosing power battery faults in new energy vehicles can significantly improve battery safety. Aiming at the collected power battery historical fault data information, a
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Practical Analysis of Application of Electronic Diagnosis Technology
power battery fault diagnosis The power source of the new energy vehicle is the battery, which is the core part of the new energy vehicle and can provide the driving power for the vehicle. If there is no battery, the new energy vehicle is a device, unable to start and drive.
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Transfer-Based Deep Neural Network for
Deep Neural Network Establishment. To observe a better pre-training model in rolling bearing fault diagnosis of new energy vehicles, this study proposes DCNNL
View more6 FAQs about [New energy battery fault diagnosis]
What is fault diagnosis of battery systems in New energy vehicles?
In this paper, the fault diagnosis of battery systems in new energy vehicles is reviewed in detail. Firstly, the common failures of lithium-ion batteries are classified, and the triggering mechanism of battery cell failure is briefly analyzed. Next, the existing fault diagnosis methods are described and classified in detail.
How to detect faults in battery systems in electric vehicles?
This paper presents a novel fault diagnosis method for battery systems in electric vehicles based on big data statistical methods. According to machine learning algorithm and 3σ multi-level screening strategy (3σ-MSS), the abnormal changes of cell terminal voltages in a battery pack can be detected and calculated in the form of probability.
How to diagnose battery system fault in real-vehicle operation conditions?
In battery system fault diagnosis, finding a suitable extraction method of fault feature parameters is the basis for battery system fault diagnosis in real-vehicle operation conditions. At present, model-based fault diagnosis methods are still the hot spot of research.
Why is accurate diagnosis of power battery faults important?
The power battery is one of the important components of New Energy Vehicles (NEVs), which is related to the safe driving of the vehicle (He and Wang 2023). Therefore, accurate diagnosis of power battery faults is an important aspect of battery safety management. At present, FDM still has the problem of inaccurate diagnosis and large errors.
How can a fault diagnosis method be used in electric vehicles?
Outlier detection algorithms are utilized for fault diagnosis verification. Quantitative battery fault analysis in the form of probability is proposed. A multi-dimensional influences in the time dimension is quantified. This paper presents a novel fault diagnosis method for battery systems in electric vehicles based on big data statistical methods.
How is a battery open fault diagnosed?
In addition, Zhou et al. also performed real-time fault diagnosis for battery open faults based on a dual-expansion Kalman filtering method, which uses only the current of the battery pack and the terminal voltages of the parallel battery modules in addition to other sensor data .
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