Lithium (Li)-ion batteries have become the mainstream energy storage solution for many applications, such as electric vehicles (EVs) and smart grids. However, various faults in a Li-ion battery system (LIBS) can potentially cause performance degradation and severe safety issues. Developing advanced fault diagnosis technologies is becoming increasingly critical for the safe operation of LIBS. This article provides a comprehensive review of the mechanisms, features, and diagnosis of various faults in LIBSs, including internal battery faults, sensor faults, and actuator faults. Future trends in the development of fault diagnosis technologies for a safer battery system are presented and discussed.

Advanced Fault Diagnosis for Lithium-Ion Battery Systems: A Review of Fault Mechanisms, Fault Features, and Diagnosis Procedures

The implementations of fuel cells (FCs) in the vehicle industry have gained great attention for the last few decades owing to simple utilization, silent operation, high efficiency and modular structure. Technological advancements show that the use of FCs in electric vehicles (EVs) will increase rapidly and cause a revolution, and will be an alternative to traditional vehicles in the future. Commercial vehicles, projects and research show that work is underway to ensure that FCEVs have sufficient performance advances for their daily transportation needs. However, the lack of a detailed study that will shed light on researchers working in this field is obvious. It aims to provide a comprehensive scientific publication on the current status and future expectations to engineers and researchers interested in this field. In the current study, numerous studies have been examined in detail and added as supplementary to the bibliography. In this context, FCEVs are classified under headings of configurations, systems components, control/management, technical challenges, marketing and future aspects. First of all, FC types and electric motors are discussed in terms of their application areas, characteristic properties and operating conditions. Power converters, which are voltage regulation and motor drive topologies used in FCEVs, are detailed according to the structural frequency of use, structure, and complexity. In the next sections, control issues for converters and technical challenges are branched for FCEVs. In final section, the current status and future aspects are reported using a large number of marketing and target data.

A review and research on fuel cell electric vehicles: Topologies, power electronic converters, energy management methods, technical challenges, marketing and future aspects

The rapid consumption of fossil fuel and increased environmental damage caused by it have given a strong impetus to the growth and development of fuel-efficient vehicles. Hybrid electric vehicles (HEVs) have evolved from their inchoate state and are proving to be a promising solution to the serious existential problem posed to the planet earth. Not only do HEVs provide better fuel economy and lower emissions satisfying environmental legislations, but also they dampen the effect of rising fuel prices on consumers. HEVs combine the drive powers of an internal combustion engine and an electrical machine. The main components of HEVs are energy storage system, motor, bidirectional converter and maximum power point trackers (MPPT, in case of solar-powered HEVs). The performance of HEVs greatly depends on these components and its architecture. This paper presents an extensive review on essential components used in HEVs such as their architectures with advantages and disadvantages, choice of bidirectional converter to obtain high efficiency, combining ultracapacitor with battery to extend the battery life, traction motors’ role and their suitability for a particular application. Inclusion of photovoltaic cell in HEVs is a fairly new concept and has been discussed in detail. Various MPPT techniques used for solar-driven HEVs are also discussed in this paper with their suitability.

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A comprehensive review on hybrid electric vehicles: architectures and components

In electric vehicles, a battery management system highly relies on the measured current, voltage, and temperature to accurately estimate state of charge (SOC) and state of health. Thus, the normal operation of current, voltage, and temperature sensors is of great importance to protect batteries from running outside their safe operating area. 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 battery pack. The difference between the true SOC and estimated SOC of each cell in the pack is defined as a residual to determine the occurrence of the fault. The true SOC is calculated by the coulomb counting method and the estimated SOC is obtained by the recursive least squares and unscented Kalman filter joint estimation method. In addition, the difference between the capacity used in SOC estimation and the estimated capacity based on the ratio of the accumulated charge to the SOC difference at two nonadjacent sampling times can also be defined as a residual for fault diagnosis. The temperature sensor which is assumed to be fault-free is used to distinguish the fault of a current or voltage sensor from the fault of a battery cell. Then, the faulty current or voltage sensor can be isolated by comparing the residual and the predefined threshold of each cell in the pack. The experimental and simulation results validate the effectiveness of the proposed sensor fault diagnosis scheme.

A Sensor Fault Diagnosis Method for a Lithium-Ion Battery Pack in Electric Vehicles

To promote the drive performance of permanent magnet synchronous machine (PMSM), such as tracking accuracy of both speed and current, one improved deadbeat-based predictive current control (DPCC) scheme based sliding mode is proposed in this paper. First, one novel PMSM model is derived by considering uncertainties of both parameters and external disturbances. Second, in order to improve the dynamic response of PMSM drive system, both sliding mode control (SMC) and DPCC are employed to control the speed and current, respectively. Third, a unified high-order sliding mode observer is designed for the estimation of disturbances and uncertainties in the speed and current loops. Furthermore, the estimated values are compensated with feedback to the designed SMC and DPCC to increase the speed robustness and current tracking accuracy. Comprehensive simulation and experiments demonstrate that the proposed control strategy is strongly robust to acute variations of load and machine parameters, and it is testified to have better speed and current tracking performance.

Improved Deadbeat Predictive Current Control Combined Sliding Mode Strategy for PMSM Drive System

Functional safety is of great importance for electric and hybrid electric vehicles (EV/HEVs). One way to improve functional safety of EV/HEVs is to develop reliable and robust onboard diagnostics (OBD) so that, once a component fault is detected, effective remedial actions are taken to avoid system failures. In this paper, we develop a systematic model-based diagnostic approach based on structural analysis for electric drive systems that can form the basis of OBD design for EVs. The structural analysis approach for fault detection and isolation (FDI) evaluates a system's structural model, using the mathematical model of the system in matrix form, from which it is possible to determine the analytic redundancy and to design the structured residuals. In this paper, we demonstrate the application of this methodology by carrying out the design of a diagnostic approach for permanent-magnet synchronous machine (PMSM) drive systems of EVs, with specific focus on sensor fault diagnosis. The diagnostic approach is first verified through a simulation study on the EcoCAR2 vehicle, which is a plug-in HEV developed by the Center for Automotive Research at The Ohio State University, and is then further validated through an experimental study on a test bench consisting of a three-phase inverter enabled by the TMS320F28035 digital signal processor and a PMSM.

Jiyu Zhang

Papers

Fault Diagnosis for Electric Drive Systems of Electrified Vehicles Based on Structural Analysis

Structural analysis based sensors fault detection and isolation of cylindrical lithium-ion batteries in automotive applications

Model-based diagnosis and fault tolerant control for ensuring torque functional safety of pedal-by-wire systems

Diagnostics and Prognostics Needs and Requirements for Electrified Vehicles Powertrains

Sensors Installation Guide to Monitor Automatic Transmission Performance