Ji Wu

Ji Wu
Hefei University of Technology · Department of Automotive Engineering

Doctor of Engineering

About

45
Publications
8,621
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
1,654
Citations
Citations since 2017
31 Research Items
1545 Citations
20172018201920202021202220230100200300400
20172018201920202021202220230100200300400
20172018201920202021202220230100200300400
20172018201920202021202220230100200300400
Additional affiliations
January 2011 - June 2016
University of Science and Technology of China
Position
  • PhD Student

Publications

Publications (45)
Article
A grid-tied micro-grid (MG) with the battery energy storage system (BESS) is studied in this paper. The energy storage efficiencies of the BESS are considered to optimize the operational cost of the MG. Two quadratic functions are verified and utilized to formulate the efficiencies of BESS in both charge and discharge process. Afterwards, constrain...
Article
The widespread use of lithium-ion batteries in electric vehicles has attracted widespread attention in both academia and industry. Among them, lithium-ion batteries' prognosis and health management are important research problems that need to be resolved urgently. This paper proposes a novel computationally efficient data-driven state of health (SO...
Article
Knowing the batteries’ health state in the electric vehicles accurately and effectively would directly enhance the system’s reliability and safety. Accordingly, this paper proposes a state of health (SOH) estimation method based on the collaboration of feature selection and machine learning methods. Specifically, actual electric vehicle data from m...
Article
Knowing the health state of the batteries would enhance the energy storage system's reliability and safety, especially for fast charge applications. Here we propose a synergetic method with the help of the genetic algorithm (GA) and the support vector regression (SVR) for SOH estimation. Firstly, features for battery aging process description are s...
Article
Accurate state of health (SOH) estimation for lithium-ion batteries is crucial to ensure the safety and reliability of electric vehicles. However, traditional neural network algorithms to estimate SOH often focus on fitting nonlinear fluctuation and is weak in the overall tracking trend. This paper thus proposes an improved radial basis function ne...
Article
Accurately monitoring battery state of charge (SOC) is essential for battery system safety. However, single and open-loop combination algorithms are mainly used for SOC estimation currently, which may have the problems of low accuracy and poor reliability. Here, a closed-loop combination algorithm with the variance-compensation extended Kalman filt...
Article
Full-text available
In this paper, an improved particle filter (Improved Particle Swarm Optimized Particle Filter, IPSO-PF) algorithm is proposed to estimate the state of charge (SOC) of lithium-ion batteries. It solves the problem of inaccurate posterior estimation due to particle degradation. The algorithm divides the particle population into three parts and designs...
Article
The state of health (SOH) plays a significant role in the mileage and safety of an electric vehicle (EV). In recent years, many methods based on data-driven analysis and laboratory measurements have been developed for SOH estimation. However, most of these proposed methods cannot be applied to real-world EVs. Here, we present a method for SOH estim...
Article
Accurate estimation of Li-ion battery state of health (SOH) is essential to ensure battery safety and vehicle operation. Here, this paper proposes a dual particle swarm optimization algorithm-extreme gradient boosting algorithm (DP-X) with the battery's charging voltage and incremental capacity (IC) data. First, the features are extracted from the...
Article
With the widespread use of lithium-ion batteries, battery failure will bring serious safety problems and economic losses. State of health (SOH) is a key and challenging issue in the prognostics and health management of lithium-ion batteries. In this paper, we propose a new SOH estimation method for lithium-ion batteries with multi-feature optimizat...
Article
Accurate state of charge (SOC) estimation is essential for the safe and reliable operation of Li-ion batteries. To solve the problem of poor generalisation caused by over-fitting, this paper presents a combination algorithm based on feature selection to estimate battery SOC. Firstly, a portion of the features is extracted from the extended Kalman f...
Article
With the widespread use of lithium-ion batteries in various fields, battery failures become the most critical concerns that may lead to enormous economic losses and even serious safety issues. The prognostics and health management of lithium-ion batteries helps to ensure reliable and safe battery operations. Existing studies on the state of health...
Article
In the long-term prediction of battery degradation, the data-driven method has great potential with historical data recorded by the battery management system. This paper proposes an enhanced data-driven model for Lithium-ion (Li-ion) battery state of health (SOH) estimation with a superior modeling procedure and optimized features. The Gaussian pro...
Article
Accurate state of health (SOH) estimation is a key issue for lithium-ion batteries management and control. In this paper, a novel SOH estimation method is proposed based on the fusion of the simulated annealing algorithm and support vector regression (SVR). Firstly, considering the electrochemical and thermodynamic characteristics of the battery ag...
Article
Considering the variabilities among each cell especially during the battery accelerated decay period, the parameterized empirical model is doubtful for predicting the Lithium-ion (Li-ion) battery Remaining Useful Life (RUL). Thus, an Empirical-Data Hybrid Driven Approach (EDHDA) is proposed to utilize both the prior knowledge and the historical dat...
Article
Battery state-of-health (SOH) estimation is a critical concern of the battery management system, which significantly affects the safe and stable operation of electric vehicles. The existing SOH estimation methods mainly focus on a single model with single-source features. Hence, the generalizability of these methods is limited. In this paper, a mul...
Article
Dear editor, This letter presents a multi-feature fusion-based method for estimating the instantaneous energy consumption of electric buses. More specifically, to improve the accuracy of instantaneous energy consumption estimation of electric buses, we propose a new energy consumption estimation method based on random forest regression (RFR) with m...
Article
Of the key parameters in the battery management system, the state of health is the most vital one concerning the distributed energy storage system's safety. Due to the limitation of the computing power of the battery management system in the actual application, a cloud-to-edge based state of health estimation method is proposed in this paper, where...
Article
Lithium-ion batteries are widely used as the power source in electric vehicles. The state of health (SOH) diagnosis is very important for the safety and storage capacity of lithium-ion batteries. In order to accurately and robustly estimate lithium-ion battery SOH, a novel long short-term memory network (LSTM) based on the charging curve is propose...
Article
Accurate state of health (SOH) estimation is critical for the durability and safety of Lithium-ion batteries (LIBs). It is challenging to predict the SOH of LIBs due to the complex aging mechanism. In this paper, a novel adaptive tunable hybrid radial basis function network is proposed for accurate and robust SOH estimation. Firstly, two Kullback-L...
Article
Accurate state-of-charge (SOC) estimation, which can effectively prevent battery overcharge and over-discharge, provide accurate driving range and extend battery life, is challenging due to complicated battery dynamics and ever-changing ambient conditions. In this paper, an extended Kalman filter (EKF) based data-driven method for SOC estimation of...
Article
Full-text available
The power distribution strategy of hybrid power sources is an important issue for fuel cell vehicles. A good power distribution control strategy can realize the optimal control of the vehicle energy, which can save energy and improve the operating conditions of the power source. Therefore, this article proposes a power distribution strategy. First,...
Article
Full-text available
In this paper, an improved method for estimating the state of charge (SOC) of lithium-ion batteries is proposed, which is developed from the particle filter (PF). An improved genetic particle filter (GPF), owing to the advantages of the PF and genetic algorithm, is proposed to overcome the disadvantage of the traditional particle filter: lacking th...
Article
Full-text available
EV和可再生能源的发展促使V2H系统成为研究的热点。EV在V2H系统中扮演着可控负载和移动储能的双重角色,具有削峰填谷、后备电源的作用,可以有效提高电网的经济性和可靠性。然而,EV行为的不确定性对微电网经济和稳定运行产生了重大影响。针对上述问题,提出了基于MCMC的方法对EV的随机性进行建模,并在此基础上建立了基于模型预测控制技术的全局在线优化算法。该算法可以在执行微电网能量优化管理的过程中充分考虑EV的储能特性,进而降低系统运行成本。不同情况下的算例分析验证了本文所提能量优化管理策略的有效性。
Article
The difference between two kinds of SOC definition is compared and analyzed. • The voltage-based SOC is estimated via PF based OCV estimation and OCV-SOC curve. • An open-loop RDT prediction framework based on SOC estimation is presented. • The accuracy of the prognostics method is validated under different conditions. A R T I C L E I N F O Keyword...
Article
A grid-tied microgrid (MG) with a battery energy storage system (BESS) is studied in this paper. The energy storage efficiencies of the BESS are considered to optimize the operational cost of the MG. Two quadratic functions are verified and utilized to formulate the efficiencies of BESS in both charge and discharge process. Afterward, constraints o...
Article
Full-text available
The state of health (SOH) of lithium-ion batteries (LIBs) is a critical parameter of the battery management system. Because of the complex internal electrochemical properties of LIBs and uncertain external working environment, it is difficult to achieve an accurate SOH determination. In this study, we proposed a novel SOH estimation method by using...
Article
The battery state of energy and state of power are two important parameters in battery usage. The state of energy represents the residual energy storage in battery and the state of power represents the ability of battery discharge/charge. To estimate the two states with high accuracy, the characteristics of battery maximum available capacity and op...
Article
The equivalent circuit model is estimated for battery states estimation. • Battery peak current is analyzed by multi-constrained conditions. • A novel multi-timescale observer is used to estimate SOE and SOP concurrently. • The accuracy of the proposed method is verified under different conditions. A B S T R A C T The battery state of energy and st...
Article
In this paper, the control theory is applied to assist the estimation of state of health (SoH) which is a key parameter to battery management. Battery can be treated as a system, and the internal state, e.g. SoH, can be observed through certain system output data. Based on the philosophy of human health and athletic ability estimation, variables fr...
Article
h i g h l i g h t s An online RUL estimation method for lithium-ion battery is proposed. RUL is described by the difference among battery terminal voltage curves. A feed forward neural network is employed for RUL estimation. Importance sampling is utilized to select feed forward neural network inputs. a b s t r a c t An accurate battery remaining u...
Conference Paper
An accurate battery model is one of the most important factors to improve the capability of battery state of charge (SoC) estimation. In this paper, battery hysteresis behaviors under different SoC are considered to decrease battery model error, and the hysteresis voltage based battery model (HVBBM) is presented. The experiment result shows that th...
Conference Paper
Full-text available
An accurate battery model is one of the most important factors to improve the capability of battery state of charge (SoC) estimation. In this paper, battery hysteresis behaviors under different SoC are considered to decrease battery model error, and the hysteresis voltage based battery model (HVBBM) is presented. The experiment result shows that th...
Article
h i g h l i g h t s The state of energy (SOE) is introduced to replace the SOC to determine the residual energy of the battery. The energy loss on the internal resistance, electrochemical reactions and decrease of OCV is considered in SOE estimation. Temperature and current influence are considered to improve the robustness of SOE estimation. The p...
Article
The state of energy (SOE) of Li-ion batteries is a critical index for energy optimization and management. In the applied battery system, the fact that the discharge current and the temperature change due to the dynamic load will result in errors in the estimation of the residual energy for the battery. To address this issue, a new method based on t...
Article
Electric vehicles (EVs) are becoming widely used for its low energy consumption and low pollution. An accurate estimation of available capacity for Li-ion batteries has an important utility significance to optimize its performance in the applications of EVs. The Peukert equation is applied to estimate the available capacity of batteries. However, t...

Network

Cited By

Projects

Projects (3)
Project
Battery Modeling; Battery States (SoC, SoE, SoP/SoF, SoH/RUL) Estimation; Battery Life Extension & Equalization; Thermal Management; Charge/Discharge Strategy; Fault Diagnosis & Alarm; Safe & Efficient Management ...
Project
Knowledge representation; behavior description; state estimation; efficient operation in management