Kai Ding

Bio: Kai Ding is an academic researcher from Hong Kong Polytechnic University. The author has contributed to research in topics: Voltage & Electric vehicle. The author has an hindex of 8, co-authored 36 publications receiving 919 citations.

Battery-Management System (BMS) and SOC Development for Electrical Vehicles

Abstract: Battery monitoring is vital for most electric vehicles (EVs), because the safety, operation, and even the life of the passenger depends on the battery system. This attribute is exactly the major function of the battery-management system (BMS)-to check and control the status of battery within their specified safe operating conditions. In this paper, a typical BMS block diagram has been proposed using various functional blocks. The state of charge (SOC) estimation has been implemented using Coulomb counting and open-circuit voltage methods, thereby eliminating the limitation of the stand-alone Coulomb counting method. By modeling the battery with SOC as one of the state variables, SOC can be estimated, which is further corrected by the Kalman filtering method. The battery parameters from experimental results are integrated in the model, and simulation results are validated by experiment.

A step-up switched-capacitor multilevel inverter with self-voltage balancing

Abstract: The objective of this paper is to propose a new inverter topology for a multilevel voltage output. This topology is designed based on a switched capacitor (SC) technique, and the number of output levels is determined by the number of SC cells. Only one dc voltage source is needed, and the problem of capacitor voltage balancing is avoided as well. This structure is not only very simple and easy to be extended to a higher level, but also its gate driver circuits are simplified because the number of active switches is reduced. The operational principle of this inverter and the targeted modulation strategies are presented, and power losses are investigated. Finally, the performance of the proposed multilevel inverter is evaluated with the experimental results of an 11-level prototype inverter.

Analysis of an asymmetric modulation method for cascaded multilevel inverters

Abstract: Traditional means for implementing the switching of the power switches in multilevel converters is subharmonic pulse width modulation (SHPWM) or triangulation approach involving a comparison between a target reference waveform and several high-frequency carrier waveforms where all the power switches usually work at high switching frequency. The asymmetric modulation method (AMM) which is derived from hybrid modulation method is illustrated. The contribution of asymmetric modulation is to provide a general method of finding the locus of the output stepped-wave for the hybrid modulation method. This study also provides an illustration of the ‘Mathematic expression of modulation process’ of SHPWM and AMM where it is easy to see how the two techniques are related, and the output expression of the AMM method can be easily obtained from the general N-level double-Fourier output expressions of SHPWM where cumbersome mathematical work has been avoided. Through the analysis of modulation process for SHPWM and AMM, results show that the AMM is an improved version of SHPWM method with optimised switching combination. Theoretical analysis, simulation and experimental results are provided to validate the feasibility of the proposed analysis method.

A Novel Detection Method for Voltage Sags

Abstract: Determining the start and end of the voltage sag event is very important for sag analysis and mitigation. There are several detection methods for voltage sags in which sag voltages are usually expressed in the terms of RMS. The RMS method represents one cycle historical average value, not instantaneous value which may lead to long detection time when voltage sag has occurred. This paper will proposed a novel voltage sag detection method based on miss voltage technique. Proper dead-band and hysteresis are used in the method. The actual instantaneous voltage is compared with certain percentage of desired grid voltage and certain percentage of the amplitude of the grid voltage. Through instantaneous value comparison, low instantaneous value of the grid is shielded which overcome the mishandling turnover of voltage sags. The approach is fully described, and the results are compared with other methods for marking the beginning and end of sag, such as RMS value evaluation method and Peak-value method and simulation result provides that the method is efficient and fast and can be used to determine the initiation and recovery of voltage sags accompanied by missing voltage technique.

Battery management system and control strategy for hybrid and electric vehicle

Abstract: Battery management system (BMS) is an integral part of any electrical vehicle, which ensures that the batteries are not subjected to conditions outside their specified safe operating conditions. Thus the safety of the battery as well as of the passengers depend on the design of the BMS. In the present work a preliminary work is carried out to simulate a typical BMS for hybrid electrical vehicle. The various functional blocks of the BMS are implemented in SIMULINK toolbox of MATLAB. The BMS proposed is equipped with a battery model in which SOC is used as one of the states to overcome the limitation of stand-alone coulomb counting method for SOC estimation. The parameters of the battery are extracted from experimental results and incorporated in the model. The simulation results are validated by experimental results.

Multi-level conversion : high voltage choppers and voltage-source inverters

Abstract: The authors discuss high-voltage power conversion. Conventional series connection and three-level voltage source inverter techniques are reviewed and compared. A novel versatile multilevel commutation cell is introduced: it is shown that this topology is safer and more simple to control, and delivers purer output waveforms. The authors show how this technique can be applied to either choppers or voltage-source inverters and generalized to any number of switches.<>

A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations

Abstract: Due to increasing concerns about global warming, greenhouse gas emissions, and the depletion of fossil fuels, the electric vehicles (EVs) receive massive popularity due to their performances and efficiencies in recent decades. EVs have already been widely accepted in the automotive industries considering the most promising replacements in reducing CO2 emissions and global environmental issues. Lithium-ion batteries have attained huge attention in EVs application due to their lucrative features such as lightweight, fast charging, high energy density, low self-discharge and long lifespan. This paper comprehensively reviews the lithium-ion battery state of charge (SOC) estimation and its management system towards the sustainable future EV applications. The significance of battery management system (BMS) employing lithium-ion batteries is presented, which can guarantee a reliable and safe operation and assess the battery SOC. The review identifies that the SOC is a crucial parameter as it signifies the remaining available energy in a battery that provides an idea about charging/discharging strategies and protect the battery from overcharging/over discharging. It is also observed that the SOC of the existing lithium-ion batteries have a good contribution to run the EVs safely and efficiently with their charging/discharging capabilities. However, they still have some challenges due to their complex electro-chemical reactions, performance degradation and lack of accuracy towards the enhancement of battery performance and life. The classification of the estimation methodologies to estimate SOC focusing with the estimation model/algorithm, benefits, drawbacks and estimation error are extensively reviewed. The review highlights many factors and challenges with possible recommendations for the development of BMS and estimation of SOC in next-generation EV applications. All the highlighted insights of this review will widen the increasing efforts towards the development of the advanced SOC estimation method and energy management system of lithium-ion battery for the future high-tech EV applications.