A Lithium-Ion Battery-in-the-Loop Approach to Test and Validate Multiscale Dual H Infinity Filters for State-of-Charge and Capacity Estimation

Cheng, Chuntian; Xiong, Rui; Shen, Weixiang

doi:10.1109/tpel.2017.2670081

Cited by 235 publications

(105 citation statements)

References 29 publications

Supporting

Mentioning

105

Contrasting

Order By: Relevance

“…The heat transfer coefficient of the battery was studied through the Harbin bus driving cycles. It can provide a theoretical basis for the design of a thermal management system in Harbin [15]. Figures 1-3 show the Harbin city road bus cycle (regular lines), Harbin bus rapid transit cycle (BRT lines), and the Harbin suburban bus cycle (suburban lines), respectively.…”

Section: Selection and Calculation Of The Test Cyclesmentioning

confidence: 99%

Determination of the Optimum Heat Transfer Coefficient and Temperature Rise Analysis for a Lithium-Ion Battery under the Conditions of Harbin City Bus Driving Cycles

Siyu

Chen

2017

Energies

View full text Add to dashboard Cite

This study investigated the heat problems that occur during the operation of power batteries, especially thermal runaway, which usually take place in high temperature environments. The study was conducted on a ternary polymer lithium-ion battery. In addition, a lumped parameter thermal model was established to analyze the thermal behavior of the electric bus battery system under the operation conditions of the driving cycles of the Harbin city electric buses. Moreover, the quantitative relationship between the optimum heat transfer coefficient of the battery and the ambient temperature was investigated. The relationship between the temperature rise (T r ), the number of cycles (c), and the heat transfer coefficient (h) under three Harbin bus cycles have been investigated at 30 • C, because it can provide a basis for the design of the battery thermal management system. The results indicated that the heat transfer coefficient that meets the requirements of the battery thermal management system is the cubic power function of the ambient temperature. Therefore, if the ambient temperature is 30 • C, the heat transfer coefficient should be at least 12 W/m 2 K in the regular bus lines, 22 W/m 2 K in the bus rapid transit lines, and 32 W/m 2 K in the suburban lines.

show abstract

Section: Selection and Calculation Of The Test Cyclesmentioning

confidence: 99%

Determination of the Optimum Heat Transfer Coefficient and Temperature Rise Analysis for a Lithium-Ion Battery under the Conditions of Harbin City Bus Driving Cycles

Siyu

Chen

2017

Energies

View full text Add to dashboard Cite

show abstract

“…The SOC estimation has been well studied in a lot of previous researches, for example, Xiong et al [26] proposed an online battery SOC estimation method. This method was applied based on the hardware-in-loop (HIL) setup, where the novel adaptive H infinity filter was proposed to realize the real-time estimation of the battery SOC.…”

Section: Online Model Parameter Identificationmentioning

confidence: 99%

Online Reliable Peak Charge/Discharge Power Estimation of Series-Connected Lithium-Ion Battery Packs

et al. 2017

View full text Add to dashboard Cite

Abstract:The accurate peak power estimation of a battery pack is essential to the power-train control of electric vehicles (EVs). It helps to evaluate the maximum charge and discharge capability of the battery system, and thus to optimally control the power-train system to meet the requirement of acceleration, gradient climbing and regenerative braking while achieving a high energy efficiency. A novel online peak power estimation method for series-connected lithium-ion battery packs is proposed, which considers the influence of cell difference on the peak power of the battery packs. A new parameter identification algorithm based on adaptive ratio vectors is designed to online identify the parameters of each individual cell in a series-connected battery pack. The ratio vectors reflecting cell difference are deduced strictly based on the analysis of battery characteristics. Based on the online parameter identification, the peak power estimation considering cell difference is further developed. Some validation experiments in different battery aging conditions and with different current profiles have been implemented to verify the proposed method. The results indicate that the ratio vector-based identification algorithm can achieve the same accuracy as the repetitive RLS (recursive least squares) based identification while evidently reducing the computation cost, and the proposed peak power estimation method is more effective and reliable for series-connected battery packs due to the consideration of cell difference.

show abstract

“…They developed an online battery monitoring method to detect battery packs and cells, which could predict cell and system performance. Chen et al [20] presented a multi-scale dual H infinity filters (HIF) method to estimate battery SOC and capacity in real-time. Compared to the single/multi-scale dual Kalman filters, this multi-scale dual HIF method had better robustness and higher estimation accuracy with experimental data of a LiMn 2 O 4 (LMO) battery.…”

Section: Introductionmentioning

confidence: 99%

Entropy-Based Voltage Fault Diagnosis of Battery Systems for Electric Vehicles

et al. 2018

View full text Add to dashboard Cite

Abstract:The battery is a key component and the major fault source in electric vehicles (EVs). Ensuring power battery safety is of great significance to make the diagnosis more effective and predict the occurrence of faults, for the power battery is one of the core technologies of EVs. This paper proposes a voltage fault diagnosis detection mechanism using entropy theory which is demonstrated in an EV with a multiple-cell battery system during an actual operation situation. The preliminary analysis, after collecting and preprocessing the typical data periods from Operation Service and Management Center for Electric Vehicle (OSMC-EV) in Beijing, shows that overvoltage fault for Li-ion batteries cell can be observed from the voltage curves. To further locate abnormal cells and predict faults, an entropy weight method is established to calculate the objective weight, which reduces the subjectivity and improves the reliability. The result clearly identifies the abnormity of cell voltage. The proposed diagnostic model can be used for EV real-time diagnosis without laboratory testing methods. It is more effective than traditional methods based on contrastive analysis.

show abstract

A Lithium-Ion Battery-in-the-Loop Approach to Test and Validate Multiscale Dual H Infinity Filters for State-of-Charge and Capacity Estimation

Cited by 235 publications

References 29 publications

Determination of the Optimum Heat Transfer Coefficient and Temperature Rise Analysis for a Lithium-Ion Battery under the Conditions of Harbin City Bus Driving Cycles

Determination of the Optimum Heat Transfer Coefficient and Temperature Rise Analysis for a Lithium-Ion Battery under the Conditions of Harbin City Bus Driving Cycles

Online Reliable Peak Charge/Discharge Power Estimation of Series-Connected Lithium-Ion Battery Packs

Entropy-Based Voltage Fault Diagnosis of Battery Systems for Electric Vehicles

Contact Info

Product

Resources

About