Wanlin Wang
Wanlin Wang has a total of 14 co-authors. Here are the top co-authors by number of shared publications:
- Changyong Jin
State Key Laboratory of Intelligent Green Vehicle and Mobility (SKLIGVM), School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China
1 shared publication - Cheng Yu
Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China
1 shared publication - Chengshan Xu
State Key Laboratory of Intelligent Green Vehicle and Mobility (SKLIGVM), School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China
1 shared publication - En Mei Jin
Department of Electrical Engineering, Chonnam National University, Gwangju, 500-757, South Korea
1 shared publication - Hal-Bon Gu
Chonnam Natl Univ, Dept Elect Engn, Gwangju 500757, South Korea
1 shared publication - Jiangna Gu
Farasis Energy (GanZhou) Co., Ltd., Ganzhou 341000, China
1 shared publication
Latest Publications
- Open Access
Development and Validation of an Electromagnetic Induction-Based Thermal Propagation Test Method for Large-Format Lithium-Ion Battery Systems
This study establishes a standardized framework for thermal propagation test in nickel-7 lithium-ion battery systems through a high-frequency electromagnetic induction heating method. The non-intrusive triggering mechanism enables precise thermal runaway initiation within two seconds through localized eddy current heating (>1200 °C), validated through cell-level tests with 100% success rate across diverse trigger positions. System-level thermal propagation tests were conducted on two identical battery boxes. The parallel experiments revealed distinct propagation patterns influenced by system sealing quality. In the inadequately sealed system (Box 01), flame formation led to accelerated thermal propagation through enhanced convective and radiative heat transfer. In contrast, the well-sealed system (Box 02) maintained an oxygen-deficient environment, resulting in a controlled sequential propagation pattern. The testing methodology incorporating dummy modules proved efficient for validating thermal protection strategies while optimizing costs. This study contributes to a deeper understanding of thermal runaway propagation mechanisms and the development of standardized testing protocols for large-format battery systems.
Open AccessDevelopment and Validation of an Electromagnetic Induction-Based Thermal Propagation Test Method for Large-Format Lithium-Ion Battery Systems
This study establishes a standardized framework for thermal propagation test in nickel-7 lithium-ion battery systems through a high-frequency electromagnetic induction heating method. The non-intrusive triggering mechanism enables precise thermal runaway initiation within two seconds through localized eddy current heating (>1200 °C), validated through cell-level tests with 100% success rate across diverse trigger positions. System-level thermal propagation tests were conducted on two identical battery boxes. The parallel experiments revealed distinct propagation patterns influenced by system sealing quality. In the inadequately sealed system (Box 01), flame formation led to accelerated thermal propagation through enhanced convective and radiative heat transfer. In contrast, the well-sealed system (Box 02) maintained an oxygen-deficient environment, resulting in a controlled sequential propagation pattern. The testing methodology incorporating dummy modules proved efficient for validating thermal protection strategies while optimizing costs. This study contributes to a deeper understanding of thermal runaway propagation mechanisms and the development of standardized testing protocols for large-format battery systems.
- Open Access
A Training-Free Estimation Method for the State of Charge and State of Health of Series Battery Packs under Various Load Profiles
To ensure the accuracy of state of charge (SOC) and state of health (SOH) estimation for battery packs while minimizing the amount of pre-experiments required for aging modeling and the scales of computation for online management, a decisive-cell-based estimation method with training-free characteristic parameters and a dynamic-weighted estimation strategy is proposed in this paper. Firstly, to reduce the computational complexity, the state estimation of battery packs is summed up to that of two decisive cells, and a new selection approach for the decisive cells is adopted based on the detection of steep voltage changes. Secondly, two novel ideas are implemented for the state estimation of the selected cells. On the one hand, a set of characteristic parameters that only exhibit local curve shrinkage with aging is chosen, which keeps the corresponding estimation approaches away from training. On the other hand, multiple basic estimation approaches are effectively combined by their respective dynamic weights, which ensures the estimation can maintain a good estimation accuracy under various load profiles. Finally, the experimental results show that the new method can quickly correct the initial setting deviations and have a high estimation accuracy for both the SOC and SOH within 2% for a series battery pack consisting of cells with obvious inconsistency.
Open AccessA Training-Free Estimation Method for the State of Charge and State of Health of Series Battery Packs under Various Load Profiles
To ensure the accuracy of state of charge (SOC) and state of health (SOH) estimation for battery packs while minimizing the amount of pre-experiments required for aging modeling and the scales of computation for online management, a decisive-cell-based estimation method with training-free characteristic parameters and a dynamic-weighted estimation strategy is proposed in this paper. Firstly, to reduce the computational complexity, the state estimation of battery packs is summed up to that of two decisive cells, and a new selection approach for the decisive cells is adopted based on the detection of steep voltage changes. Secondly, two novel ideas are implemented for the state estimation of the selected cells. On the one hand, a set of characteristic parameters that only exhibit local curve shrinkage with aging is chosen, which keeps the corresponding estimation approaches away from training. On the other hand, multiple basic estimation approaches are effectively combined by their respective dynamic weights, which ensures the estimation can maintain a good estimation accuracy under various load profiles. Finally, the experimental results show that the new method can quickly correct the initial setting deviations and have a high estimation accuracy for both the SOC and SOH within 2% for a series battery pack consisting of cells with obvious inconsistency.
- Open Access
- 2 February 2012
- Published by Springer Nature in Discover Nano
- Vol. 7 (1) , 98
Increases in solar conversion efficiencies of the ZrO2 nanofiber-doped TiO2 photoelectrode for dye-sensitized solar cells
In this paper, in order to improve the efficiency of dye-sensitized solar cells, we introduced zirconia [ZrO2] nanofibers into a mesoporous titania [TiO2] photoelectrode. The photoelectrode consists of a few weight percent of ZrO2 nanofibers and a mesoporous TiO2 powder. The mixed ZrO2 nanofibers and the mesoporous TiO2 powder possessed a larger surface area than the corresponding mesoporous TiO2 powder. The optimum ratio of the ZrO2 nanofiber was 5 wt.%. The 5 wt.% ZrO2-mixed device could get a short-circuit photocurrent density of 15.9 mA/cm2, an open-circuit photovoltage of 0.69 V, a fill factor of 0.60, and a light-to-electricity conversion efficiency of 6.5% under irradiation of AM 1.5 (100 mW/cm2).
- 2 February 2012
- Published by Springer Nature in Discover Nano
- Vol. 7 (1) , 98
Open AccessIncreases in solar conversion efficiencies of the ZrO2 nanofiber-doped TiO2 photoelectrode for dye-sensitized solar cells
In this paper, in order to improve the efficiency of dye-sensitized solar cells, we introduced zirconia [ZrO2] nanofibers into a mesoporous titania [TiO2] photoelectrode. The photoelectrode consists of a few weight percent of ZrO2 nanofibers and a mesoporous TiO2 powder. The mixed ZrO2 nanofibers and the mesoporous TiO2 powder possessed a larger surface area than the corresponding mesoporous TiO2 powder. The optimum ratio of the ZrO2 nanofiber was 5 wt.%. The 5 wt.% ZrO2-mixed device could get a short-circuit photocurrent density of 15.9 mA/cm2, an open-circuit photovoltage of 0.69 V, a fill factor of 0.60, and a light-to-electricity conversion efficiency of 6.5% under irradiation of AM 1.5 (100 mW/cm2).