Adaptive unscented Kalman filter based state of energy and power capability estimation approach for lithium-ion battery

Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs

Plett, G. L. (2004) · Journal of Power Sources · doi:10.1016/j.jpowsour.2004.02.032 · Cited by 1,927

Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs

Plett, G. L. (2004) · Journal of Power Sources · doi:10.1016/j.jpowsour.2004.02.033 · Cited by 1,768

Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs

Plett, G. L. (2004) · Journal of Power Sources · doi:10.1016/j.jpowsour.2004.02.031 · Cited by 1,385

The state of the art of electric and hybrid vehicles

Chan, C. C. (2002) · Proceedings of the IEEE · doi:10.1109/5.989873 · Cited by 1,102

A data-driven multi-scale extended Kalman filtering based parameter and state estimation approach of lithium-ion polymer battery in electric vehicles

Xiong, R., Sun, F., Chen, Z., & He, H. (2013) · Applied Energy · doi:10.1016/j.apenergy.2013.07.061 · Cited by 529

Online estimation of internal resistance and open-circuit voltage of lithium-ion batteries in electric vehicles

Chiang, Y., Sean, W., & Ke, J.-C. (2011) · Journal of Power Sources · doi:10.1016/j.jpowsour.2011.01.005 · Cited by 393

High-Performance Battery-Pack Power Estimation Using a Dynamic Cell Model

Plett, G. L. (2004) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2004.832408 · Cited by 290

Adaptive Partial Differential Equation Observer for Battery State-of-Charge/State-of-Health Estimation Via an Electrochemical Model

Moura, S. J., Chaturvedi, N. A., & Krstić, M. (2013) · Journal of Dynamic Systems Measurement and Control · doi:10.1115/1.4024801 · Cited by 262

A modified model based state of charge estimation of power lithium-ion batteries using unscented Kalman filter

Tian, Y., Xia, B., Sun, W., Xu, Z., & Zheng, W. (2014) · Journal of Power Sources · doi:10.1016/j.jpowsour.2014.07.143 · Cited by 229

A data-driven based adaptive state of charge estimator of lithium-ion polymer battery used in electric vehicles

Xiong, R., Sun, F., Gong, X., & Gao, C. (2013) · Applied Energy · doi:10.1016/j.apenergy.2013.09.006 · Cited by 229

Research on Multi-Time Scale SOP Estimation of Lithium–Ion Battery Based on H∞ Filter

Li, R., Li, K., Liu, P., & Zhang, X. (2023) · Batteries · doi:10.3390/batteries9040191 · Cited by 20

Improved joint prediction strategy for state of charge and peak power of lithium-ion batteries by considering hysteresis characteristics-current measurement deviation correction

Qi, C., Wang, S., Cao, W., Wang, Y., Liu, D., & Fernández, C. (2024) · Journal of Energy Storage · doi:10.1016/j.est.2024.110726 · Cited by 18

Maximum Available Capacity and Energy Estimation Based on Support Vector Machine Regression for Lithium-ion Battery

Deng, Z., Yang, L., Cai, Y., & Deng, H. (2017) · Energy Procedia · doi:10.1016/j.egypro.2016.12.131 · Cited by 18

Innovative Modeling Approach for Li-Ion Battery Packs Considering Intrinsic Cell Unbalances and Packaging Elements

Ko, S.-T., Lee, J., Ahn, J.-H., & Lee, B. (2019) · Energies · doi:10.3390/en12030356 · Cited by 18

A SOE estimation method for lithium batteries considering available energy and recovered energy

Peng, H. L., Wang, C., Zhao, W., Wang, W., Wu, G., & Chang, C. (2022) · Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering · doi:10.1177/09544070211070441 · Cited by 16

Adaptive Kalman Filter-Based Single-Beacon Underwater Tracking with Unknown Effective Sound Velocity

Deng, Z., Yu, X., Qin, H., & Zhu, Z. (2018) · Sensors · doi:10.3390/s18124339 · Cited by 16

An SOE estimation model considering electrothermal effect for LiFePO4/C battery

Lin, S., Song, W., Lv, J., Feng, Z., Zhang, Y., & Li, Y. (2017) · International Journal of Energy Research · doi:10.1002/er.3818 · Cited by 16

Cloud-Battery management system based health-aware battery fast charging architecture using error-correction strategy for electric vehicles

Bose, B., Shaosen, S., Li, W., Gao, L., Wei, K., & Garg, A. (2023) · Sustainable Energy Grids and Networks · doi:10.1016/j.segan.2023.101197 · Cited by 15

Joint SOC–SOP estimation method for lithium-ion batteries based on electro-thermal model and multi-parameter constraints

Qin, P., Che, Y., Li, H., Cai, Y., & Jiang, M. (2022) · Journal of Power Electronics · doi:10.1007/s43236-021-00376-9 · Cited by 15

A Remaining Discharge Energy Prediction Method for Lithium-Ion Battery Pack Considering SOC and Parameter Inconsistency

Fang, Q., Wei, X., & Dai, H. (2019) · Energies · doi:10.3390/en12060987 · Cited by 15

Review of State of Power Estimation for Li-Ion Batteries: Methods, Issues, and Prospects

Ma, W., Ren, S., & Guo, P. (2024) · Journal of Electrochemical Science and Technology · doi:10.33961/jecst.2024.00724 · Cited by 14

Estimating power capability of aged lithium-ion batteries in presence of communication delays

Fridholm, B., Wik, T., Kuusisto, H., & Klintberg, A. (2018) · Journal of Power Sources · doi:10.1016/j.jpowsour.2018.02.018 · Cited by 14

Remaining useful life prediction of lithium-ion battery using a hybrid model-based filtering and data-driven approach

Zheng, X., Wu, H., & Chen, Y. (2017) · Asian Control Conference (ASCC) · doi:10.1109/ascc.2017.8287603 · Cited by 14

A Novel Temperature–Hysteresis Model for Power Battery of Electric Vehicles with an Adaptive Joint Estimator on State of Charge and Power

Lei, X., Zhao, X., Wang, G., & Liu, W. (2019) · Energies · doi:10.3390/en12193621 · Cited by 14

Estimation of state‐of‐energy for lithium batteries based on dual adaptive particle filters considering variable current and noise effects

Zhang, Z., Zhang, X., Mao, S., Huai, R., & Yu, Z. (2021) · International Journal of Energy Research · doi:10.1002/er.6823 · Cited by 13

Identification and Fast Measurement Method of Open-circuit Voltage

Peng, L., Jin, P., & Zhang, H. (2023) · Journal of The Electrochemical Society · doi:10.1149/1945-7111/acc2ec · Cited by 12

State-of-Charge Estimation of Lithium-ion Battery Based on Capacity Degradation Model Considering the Dynamic Currents and Temperatures

Gao, Y., Huang, R., Qin, D., Wang, T., Ma, S., & Qin, S. (2021) · International Journal of Electrochemical Science · doi:10.20964/2021.04.09 · Cited by 12

Robust SLAM: SLAM base on $$\hbox {H}_{\infty }$$ H ∞ square root unscented Kalman filter

Havangi, R. (2015) · Nonlinear Dynamics · doi:10.1007/s11071-015-2365-x · Cited by 12

State of charge and parameters estimation for Lithium-ion battery using dual adaptive unscented Kalman filter

Guo, H., Wang, Z., Li, Y., Wang, D., & Wang, G. (2017) · Chinese Control and Decision Conference (CCDC) · doi:10.1109/ccdc.2017.7979374 · Cited by 12

An Improved Model Equation Based on a Gaussian Function Trinomial for State of Charge Estimation of Lithium-ion Batteries

Linghu, J., Kang, L., Liu, M., Hu, B., & Wang, Z. (2019) · Energies · doi:10.3390/en12071366 · Cited by 12

State-of-X estimation for lithium-ion batteries in electric vehicles: A comprehensive review of methods, challenges, and emerging trends

Ibrahim, A.-W., Al-Shamma’a, A. A., Farh, H. M. H., Shi, Z., Abu-Rub, P. D. H., Kotb, H., & Mekhilef, S. (2026) · Journal of Energy Storage · doi:10.1016/j.est.2026.120976 · Cited by 14

Determination of the load capability for a lithium-ion battery pack using two time-scale filtering

Dong, G., & Wei, J. (2020) · Journal of Power Sources · doi:10.1016/j.jpowsour.2020.229056 · Cited by 11

A Temperature-Based Peak Power Capability Estimation Method for Lithium-Ion Batteries

Jiang, W.-J., Zhang, N., Li, P., & Chen, N. (2017) · Procedia Engineering · doi:10.1016/j.proeng.2017.04.372 · Cited by 11

Unscented Particle Filter Based State of Energy Estimation for LiFePO4 Batteries Using an Online Updated Model

Wei, X., Jun, C., Gu, Y. J., Ma, J., & Chang, J. (2022) · International Journal of Automotive Technology · doi:10.1007/s12239-022-0046-6 · Cited by 10

Online maximum discharge power prediction for lithium-ion batteries with thermal safety constraints

Wang, L., Song, Y., Lyu, C., Yang, D., Wan, M., & Ge, Y. (2023) · Journal of Energy Storage · doi:10.1016/j.est.2023.108041 · Cited by 10

Contactless Li-Ion Battery Voltage Detection by Using Walabot and Machine Learning

Wang, Y., Niu, H., Zhao, T., Liao, X., Dong, L., & Chen, Y. (2019) · doi:10.1115/detc2019-97668 · Cited by 9

A Self-Calibration SOC Estimation Method for Lithium-Ion Battery

Fu, Y., & Fu, H. (2023) · IEEE Access · doi:10.1109/access.2023.3266663 · Cited by 9

Adaptive Unscented Kalman Filter using Maximum Likelihood Estimation

Mahmoudi, Z., Poulsen, N. K., Madsen, H., & Jørgensen, J. B. (2017) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2017.08.356 · Cited by 9

Online Adaptive Covariance Estimation Approach for Multiple Odometry Sensors Fusion

Osman, M., Hussein, A., Al-Kaff, A., García, F., & Armingol, J. M. (2018) · IEEE Intelligent Vehicles Symposium · doi:10.1109/ivs.2018.8500610 · Cited by 9

Energy flow estimation-control of two interconnected microgrids

Tungadio, D. H., Bansal, R. C., & Siti, M. W. (2018) · Journal of Energy in Southern Africa · doi:10.17159/2413-3051/2017/v29i4a2439 · Cited by 9

Experimental analysis and modeling of temperature dependence of lithium-ion battery direct current resistance for power capability prediction

Zheng, L., Zhu, J. G., Wang, G., Lu, D. D., McLean, P., & He, T. (2017) · International Conference on Electrical Machines and Systems (ICEMS) · doi:10.1109/icems.2017.8056426 · Cited by 9

Bayesian filtering techniques for state of charge and state of health estimation in lithium-ion batteries for electric vehicles: Methods, challenges, and future directions

Kham, S. L., & Aunsri, N. (2026) · Applied Energy · doi:10.1016/j.apenergy.2026.128015 · Cited by 9

Stochastic dynamic modeling of lithium battery via expectation maximization algorithm

Wang, W., Liu, X., Cai, F., & Wang, J. (2015) · Neurocomputing · doi:10.1016/j.neucom.2015.10.075 · Cited by 7

Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques

Lipu, M. S. H., Hussain, A., Saad, M. H. M., & Hannan, M. A. (2017) · doi:10.1109/iceei.2017.8312418 · Cited by 7

An Overview of Peak Power Benchmark Methods for Lithium-Ion Battery

Dai, Y., Meng, J., Peng, Q., Liu, T., Cai, Y., & Wu, C. (2022) · International Conference on Smart Power & Internet Energy Systems (SPIES) · doi:10.1109/spies55999.2022.10082123 · Cited by 5

A robust identification method for inherent parameters of lithium battery considering thermal distribution and state of charge

Xu, B., Lu, X., & Bai, Y. (2023) · Journal of Energy Storage · doi:10.1016/j.est.2023.109284 · Cited by 5

A method for deriving battery one-way efficiencies

Bobanac, V., Bašić, H., & Pandžić, H. (2023) · Journal of Energy Storage · doi:10.1016/j.est.2023.108815 · Cited by 5

Energy flow estimation-control of two interconnected microgrids

Tungadio, D. H., Bansal, R. C., & Siti, M. W. (2018) · Journal of Energy in Southern Africa · doi:10.17159/2413-3051/2018/v29i4a2439 · Cited by 5

Remaining discharge energy estimation of lithium-ion batteries based on average working condition prediction and multi-parameter updating

Lai, X., Weng, J., Yang, Y., Qiu, C., Huang, Y., Yuan, M. H., Yao, Y., & Zheng, Y. (2023) · Journal of Solid State Electrochemistry · doi:10.1007/s10008-023-05683-8 · Cited by 4

Adaptive estimation for time-varying state-of-charge of lithium-ion battery with consideration of temperature distribution

Xu, B., Lu, X., Bai, Y., Xu, J., & Luo, W. (2023) · Nonlinear Dynamics · doi:10.1007/s11071-023-08735-w · Cited by 4

Remote SOC and SOH Estimation of High Energy Lithium Batteries Based on Dual-Mode Extended Kalman Filter Algorithm

Xu, R. (2024) · International Journal of High Speed Electronics and Systems · doi:10.1142/s0129156425400737 · Cited by 4

Co-estimation of states and parameters for ultracapacitors of various aging conditions using unscented Kalman filter and recursive least squares

Chiang, C.-J., Verma, P., & Tsai, S.-H. (2025) · Journal of Energy Storage · doi:10.1016/j.est.2025.116588 · Cited by 4

Simple indirect forecast of remaining discharge energy of lithium-ion battery under future complex discharge conditions

Liu, C., Hu, M., Jin, G., Fu, C., Yang, H., & Jia, Q. (2022) · Journal of Energy Storage · doi:10.1016/j.est.2022.104566 · Cited by 4

A Hybrid Adaptive Unscented Kalman Filter AlgorithmPreprint

He, J., Zhang, Q., Hu, Q., & Sun, G. (2017) · Preprints.org · doi:10.20944/preprints201703.0127.v1 · Cited by 4

Energy State Estimation for Series-Connected Battery Packs Based on Online Curve Construction of Pack Comprehensive OCV

Pei, L., Wu, Y., Shen, X., Yu, C. L., Wen, Z., & Wang, T. (2025) · Energies · doi:10.3390/en18071772 · Cited by 3

Research on Multiple States Joint Estimation Algorithm for Electric Vehicles Under Charge Mode

Wang, L., Wang, L., Liao, C., & Zhang, W. (2018) · IEEE Access · doi:10.1109/access.2018.2849419 · Cited by 3

State of Energy Estimation of Li-Ion Batteries Using Deep Neural Network and Support Vector Regression

Kumar, P., Rafat, Y., Cicconi, P., & Alam, M. S. (2022) · Springer eBooks · doi:10.1007/978-981-16-7723-6_16 · Cited by 3

A Method for Remaining Discharge Energy Prediction of Lithium-Ion Batteries Based on Terminal Voltage Prediction Model

Cao, Y., Wei, X., Dai, H., & Fang, Q. (2017) · IEEE Vehicle Power and Propulsion Conference (VPPC) · doi:10.1109/vppc.2017.8330859 · Cited by 3

State of charge and state of power estimation for power battery in HEV based on optimized particle filtering

Niu, X., & Feng, G. (2020) · Journal of Computational Methods in Sciences and Engineering · doi:10.3233/jcm-204537 · Cited by 3

State of Charge Estimation Accuracy in Charge Sustainable Mode of Hybrid Electric Vehicles

Mansour, I., Frisk, E., Jemni, A., Krysander, M., & Liouane, N. (2017) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2017.08.274 · Cited by 3

A hybrid adaptive unscented Kalman filter algorithm

He, J., Chen, Y., Zhang, Z., Yin, W., & Chen, D. (2019) · International Journal for Engineering Modelling · doi:10.31534/engmod.2018.3.ri.04d · Cited by 3

Ant Colony Particle Filter Based State of Energy Estimation Method for Lithium-ion Batteries

Liu, X., Zheng, C., Wu, J., He, Y., & Liu, X. (2020) · International Conference on Advanced Robotics and Mechatronics (ICARM) · doi:10.1109/icarm49381.2020.9195359 · Cited by 3

A review of model-based state of power estimation for lithium-ion batteries

Lu, J., Xiong, Y., Wu, X., Zhang, X., Wu, X., & Gong, F. (2026) · Journal of Energy Storage · doi:10.1016/j.est.2026.122585 · Cited by 2

State estimation of lithium-ion battery based on Gaussian process regression

Li, J., Jiao, S., Ye, M., & Wei, M. (2020) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1633/1/012090 · Cited by 2

A comparative study of extended Kalman filter and AH approach or the state of charge estimation applied in lithium batteries of electric vehicles

Nasri, E., Jarou, T., Benchikh, S., Lamrani, R., & Idrissi, S. E. (2023) · AIP conference proceedings · doi:10.1063/5.0149462 · Cited by 3

Kalman Filter Tuning for State Estimation of Lithium‐Ion Batteries by Multi‐Objective Optimization via Hyperspace Exploration

Mößle, P., Tietze, T., & Danzer, M. A. (2023) · Energy Technology · doi:10.1002/ente.202300796 · Cited by 2

A Cloud-based Aging Considered Vehicle-mounted Lithium-ion Battery Management Method: A Big Data Perspective

Li, S., He, H., & Li, J. (2019) · DEStech Transactions on Environment Energy and Earth Science · doi:10.12783/dteees/iceee2019/31803 · Cited by 2

Online Estimation of Model Parameters of Lithium-Ion Battery Using the Cubature Kalman Filter

Tian, Y., Yan, R., Tian, J., Zhou, S., & Hu, C. K. (2017) · IOP Conference Series Earth and Environmental Science · doi:10.1088/1755-1315/94/1/012051 · Cited by 2

Available peak power prediction algorithm of Li-ion battery using piecewise-linear OCV model

Goh, T., Park, M., Seo, M., & Kim, S. W. (2018) · International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM) · doi:10.1109/speedam.2018.8445385 · Cited by 2

Li-ion Battery State of Charge (SOC) and State of Health (SOH) Online Estimations Using Partial Charge or Discharge Data

Bavand, A. (2021) · ERA: Education and Research Archive (University of Alberta) · doi:10.7939/r3-eyvv-qh93 · Cited by 2

A Comparative Analysis of Online Update Techniques for Battery Model Parameters Considering Complexity and Estimation Accuracy

Han, H.-C., Noh, T.-W., & Lee, B. (2019) · International Conference on Power Electronics and ECCE Asia (ICPE-ECCE Asia) · doi:10.23919/icpe2019-ecceasia42246.2019.8797283 · Cited by 1

Estimating State of Energy in Lithium-ion Batteries Using a Super-Twisting Algorithm-Based Sliding Mode Observer*

Feng, Y., Wang, Y., Bai, F., Cao, Z., & Han, F. (2024) · Annual Conference of the IEEE Industrial Electronics Society (IECON) · doi:10.1109/iecon55916.2024.10905812 · Cited by 1

A Novel Parameter Identification Method for SOC Estimation of Lithium-Ion Batteries based on Spatiotemporal Coupling Strategy

Dou, W., Yang, Y., & Cui, X. (2025) · Journal of The Electrochemical Society · doi:10.1149/1945-7111/adf9d1 · Cited by 1

Extended and Unscented Kalman Filter Variants for Tracking the State of Charge of PV Battery Systems

Rahman, S., & Adhikari, K. (2025) · International Conference on Electrical, Computer and Energy Technologies (ICECET) · doi:10.1109/icecet63943.2025.11472367 · Cited by 1

Intelligent digital twin for real-time remaining useful life prediction of lithium-ion batteries with cumulative incremental learning and ensemble strategy

Haghighi, M., Mohammadi, M., & Allahbakhshi, M. (2026) · Results in Engineering · doi:10.1016/j.rineng.2026.111961 · Cited by 1

A composite estimation method for state of charge of batteries in a power station engineering

Chen, Y., Yang, Z., Guo, L., Huang, X., & Wang, Y. (2017) · IEEE Conference on Energy Internet and Energy System Integration (EI2) · doi:10.1109/ei2.2017.8245750 · Cited by 1

Estimation of remaining energy and available power for Li-Ion battery packs considering energy consumption by heat convection

Zheng, Y., Wang, C., Sang, S., & Yu, S. Q. (2022) · Journal of Power Electronics · doi:10.1007/s43236-022-00523-w · Cited by 1

Simulation Performance Enhancement in Automotive Embedded Control Using the Unscented Transform

Paredes, A. E. O., Nunes, L. R., Santos, M. M. D., de Menezes, L. R. A. X., Linares, K. S. C., Justo, J. F., & Gu, Z. (2019) · IEEE Access · doi:10.1109/access.2019.2917931 · Cited by 1

Online estimation of key battery states for management of vanadium redox flow battery

Wei, Z. (2017) · doi:10.32657/10356/72150

Propagating transport-code input parameter uncertainties with deterministic sampling

Sahlberg, A., Hellesen, C., Eriksson, J., Conroy, S. W., Ericsson, G., King, D., & Contributors, J. (2018) · Plasma Physics and Controlled Fusion · doi:10.1088/1361-6587/aae80b

A Study on Development of BMS module Algorithm for Bluetooth-based Lithium-Iron Phosphate Battery pack

Kim, J., & Ryu, G.-S. (2021) · Journal of the Korean Chemical Society · doi:10.15207/jkcs.2021.12.4.001

Robust Charging and Discharging Coordination of Electric Vehicles with State Dynamics Uncertainties

Wang, P., Zou, S., Zhang, J., & Ma, Z. (2022) · International Journal of Control Automation and Systems · doi:10.1007/s12555-021-0298-3

SOE and SOS Estimation

Yang, S., Liu, X., Shen, L., & Zhang, C. (2022) · Key Technologies on New Energy Vehicles · doi:10.1007/978-981-19-3490-2_8

A Review of Estimation Methods for the State of Energy of Lithium Batteries for Electric Vehicles

Yu, X., Yu, X., Lin, S., Xu, R., & Zang, H. (2023) · IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia) · doi:10.1109/icpsasia58343.2023.10294428

Electrochemical Terminology | State-of-Charge (SoC)

Wenzl, H., Benger, R., & Hauer, I. (2024) · Elsevier eBooks · doi:10.1016/b978-0-323-96022-9.00094-3

Control Barrier Functions for State of Power Estimation in Lithium-Ion Battery Management

Kossek, M., & Trimboli, M. S. (2026) · Journal of Dynamic Systems Measurement and Control · doi:10.1115/1.4071370

Control and scheduling of hybrid hydropower plants with batteries for enhanced flexibility in future power systems

Cassano, S. (2023) · doi:10.70675/52e46d36z074bz4ffbz827bz35f3dfe51ec2

State-of-Energy Estimation of a Lithium Iron Phosphate Battery Usingan Iterated CKF–EKF Algorithm

Xiao, M., Li, M., Kang, J., & 田中 (2026) · Batteries · doi:10.3390/batteries12100397

States Estimation of Li-ion Power Batteries Based on Adaptive Unscented Kalman Filters

Kexi, W. (2014) · Proceedings of the CSEE · Cited by 16

A method for state of charge and state of health estimation of lithium-ion battery based on adaptive unscented Kalman filter

Liu, S., Dong, X., Yu, X., Ren, X., Zhang, J., & Zhu, R. (2022) · Energy Reports · doi:10.1016/j.egyr.2022.09.093 · Cited by 56

The Power State Estimation Method for High Energy Ternary Lithium-ion Batteries Based on the Online Collaborative Equivalent Modeling and Adaptive Correction - Unscented Kalman Filter

Fan, Y., Wang, S., Jiang, C. F., & Fernández, C. (2020) · International Journal of Electrochemical Science · doi:10.20964/2021.01.70 · Cited by 3

A Method for State-of-Charge Estimation of Lithium-Ion Batteries Based on Adaptive Unscented Kalman FiltePreprint

Liu, S., Huang, K., & Feng, J. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.5004165

State of Energy Estimation Based on AUKF for Lithium Battery Used on Pure Electric Vehicle

Liu, H. W., Wang, H. F., & Guo, C. (2012) · Advanced materials research · doi:10.4028/www.scientific.net/amr.608-609.1627 · Cited by 5