Journal Publications 1. Su, S., Li, W., Mou, J., *Garg, A., Gao, L., & Liu, J. (2022). A hybrid battery equivalent circuit model, deep learning, and transfer learning for battery state monitoring. IEEE Transactions on Transportation Electrification, 9(1), 1113-1127. (SCI)2. Li, W., Xiao, M., Garg, A., & Gao, L. (2020). A new approach to solve uncertain multidisciplinary design optimization based on conditional value at risk. IEEE Transactions on Automation Science and Engineering, 18(1), 356-368. (SCI)3. Bose, B., *Garg, A., Gao, L., Kim, J., & Singh, S. (2023). Development of novel MSCCCTCV charging strategy for health-aware battery fast charging using QOGA optimization. IEEE Transactions on Transportation Electrification.4. Patra, S., Chandra K, P., Li, W., Mou, J., Gao, L., Zhou, Q., & *Garg, A. (2023). Performance study of cooling plates with single and double outlets for lithium-ion battery thermal management system based on topology optimization. International Journal of Green Energy, 1-19.5. Zhong, Q., Chandra, P. K., Li, W., Gao, L., Garg, A., Lv, S., & Tai, K. (2023). A Comprehensive Numerical study based on Topology Optimization for Cooling plates Thermal Design of Battery Packs. Applied Thermal Engineering, 121918.6. Chen, P., Li, W., Gao, L. I. A. N. G., & *Garg, A. A comprehensive review on topology optimization of liquid cooling plates for lithium-ion battery packs. Annual Review of Heat Transfer.7. Lu, L., Sobrido, A. J., Gao, L., *Garg, A., & Li, W. (2023). A comprehensive study on physics-based simulation combined multi-objective optimization of capacity decay and voltage loss of Vanadium redox flow battery. Electrochimica Acta, 468, 143151.8. Su, S., Li, W., *Garg, A., & Gao, L. (2022). An adaptive boosting charging strategy optimization based on thermoelectric-aging model, surrogates and multi-objective optimization. Applied Energy, Elsevier, 312, 118795. (SCI)9. Bibaswan, B., Shaosen, S., Li, W., Gao, L., Wei, K., & *Garg, A. (2023). Cloud-Battery management system based health-aware battery fast charging architecture using error-correction strategy for Electric Vehicles. Sustainable Energy, Grids and Networks, 101197.10. Lan, T. H., Wang, C. T., Sangeetha, T., Yang, Y. C., & Garg, A. (2018). Constructed mathematical model for nanowire electron transfer in microbial fuel cells. Journal of Power Sources, 402, 483-488. (SCI)11. Li, W., Garg, A., Wang, N., Gao, L., Le Phung, M. L., & Tran, V. M. (2022). Computational fluid dynamics-based numerical analysis for studying the effect of mini-channel cooling plate, flow characteristics, and battery arrangement for cylindrical lithium-ion battery pack. ASME Journal of Electrochemical Energy Conversion and Storage, 19(4), 041003. (SCI)12. Garg, A., Mou, J., Su, S., & Gao, L. (2022). Reconfigurable battery systems: Challenges and safety solutions using intelligent system framework based on digital twins. IET Collaborative Intelligent Manufacturing, IET Publisher, 4(3), 232-248. (SCI)13. Thomas, A. S., Garg, A., Kim, J., Panigrahi, B. K., & Le Phung, M. L. (2022). Study on efficacy of different heat transfer fluids flowing through an aluminium flow plate channel on the temperature of the prismatic lithium-ion battery pack. Journal of Energy Storage, Elsevier, 52, 105059. (SCI)14. Wang, N., Garg, A., Su, S., Mou, J., Gao, L., & Li, W. (2022). Echelon utilization of retired power lithium-ion batteries: Challenges and prospects. Batteries, MDPI 8(8), 96. (SCI)15. Li, Y., Garg, A., Shevya, S., Li, W., Gao, L., & Lee Lam, J. S. (2022). A hybrid convolutional neural network-long short term memory for discharge capacity estimation of lithium-ion batteries. ASME Journal of Electrochemical Energy Conversion and Storage, 19(3), 030901. (SCI)16. Chandra K, P., Jishnu, A. K., Garg, A., Panigrahi, B. K., & Singh, S. (2022). Heat transfer augmentation of lithium‐ion battery packs by incorporating an interrupted fin arrangement. International Journal of Energy Research, 46(10), 14371-14395. (SCI)17. Ghosh, N., Garg, A., Li, W., Gao, L., & Nguyen-Thoi, T. (2022). Engineering design of battery module for electric vehicles: comprehensive framework development based on density functional theory, topology optimization, machine learning, multidisciplinary design optimization, and digital twins. ASME Journal of Electrochemical Energy Conversion and Storage, 19(3), 030902. (SCI)18. Singh, M., Bansal, S., Vandana, Panigrahi, B. K., & Garg, A. (2022). A genetic algorithm and RNN-LSTM model for remaining battery capacity prediction. ASME Journal of Computing and Information Science in Engineering, 22(4), 041009. (SCI)19. Li, W., Gao, L., Garg, A., & Xiao, M. (2022). Multidisciplinary robust design optimization considering parameter and metamodeling uncertainties. Engineering with Computers, 1-18. (SCI)20. Peng, X., Li, Y., Yang, W., & Garg, A. (2021). Real-time state of charge estimation of the extended Kalman filter and unscented Kalman filter algorithms under different working conditions. ASME Journal of Electrochemical Energy Conversion and Storage, 18(4), 041007. (SCI)21. Vyas, M., Pareek, K., Sapre, S., & Garg, A. (2021). Single point diagnosis of short circuit abuse condition in lithium‐ion battery through impedance data. International Journal of Energy Research, 45(12), 18212-18221. (SCI)22. Li, Y., Li, C., Garg, A., Gao, L., & Li, W. (2021). Heat dissipation analysis and multi-objective optimization of a permanent magnet synchronous motor using surrogate assisted method. Case Studies in Thermal Engineering, 27, 101203. (SCI)23. Tran, T. N., Garg, A., Phung, T. G., Le, M. L. P., & Panwar, N. G. (2021). Machine learning technique-based data-driven model of exploring effects of electrolyte additives on LiNi0. 6Mn0. 2Co0. 2O2/graphite cell. Journal of Energy Storage, 42, 103012. (SCI)24. Su, S., Li, W., Li, Y., Garg, A., Gao, L., & Zhou, Q. (2021). Multi-objective design optimization of battery thermal management system for electric vehicles. Applied Thermal Engineering, 196, 117235. (SCI)25. Huang, Y., Su, Y., & Garg, A. (2021). Measurement and prediction of decomposed energy efficiencies of lithium ion batteries with two charge models. ASME Journal of Electrochemical Energy Conversion and Storage, 18(3), 030901. (SCI)26. Chen, S., Bao, N., Garg, A., Peng, X., & Gao, L. (2021). A fast charging–cooling coupled scheduling method for a liquid cooling-based thermal management system for lithium-ion batteries. Engineering, 7(8), 1165-1176. (SCI)27. Panwar, N. G., Singh, S., Garg, A., Gupta, A. K., & Gao, L. (2021). Recent advancements in battery management system for Li‐ion batteries of electric vehicles: future role of digital twin, cyber‐physical systems, battery swapping technology, and nondestructive testing. Energy Technology, 9(8), 2000984. (SCI)28. Gao, L., & Garg, A. (Eds.). (2021). Special Section on Degradation Prediction and Recycling of Renewable Energy and Energy Storage Systems: Scenarios of 2020–2025. ASME Journal of Electrochemical Energy Conversion and Storage, 18(3), 030301. (SCI)29. Garg, A., LE, M., Nguyen, T. N. H., Singh, S., Goyal, A., Tran, V. M., ... & Nguyen, V. H. (2021). Electrochemical performance enhancement of Sodium-Ion batteries fabricated with NaNi1/3Mn1/3Co1/3O2 cathodes using support vector Regression-Simplex algorithm approach, DOI:10.1115/1.404435830. Nguyen-Thoi, T., Cui, X., Garg, A., Gao, L., & Truong, T. T. (2021). An effective deep neural network method for prediction of battery state at cell and module level. Energy Technology, 9(7), 2100048. (SCI)31. Tan, W. J., Chin, C. M. M., Garg, A., & Gao, L. (2021). A hybrid disassembly framework for disassembly of electric vehicle batteries. International Journal of Energy Research, 45(5), 8073-8082. (SCI)32. Garg, A., Liu, C., Jishnu, A. K., Gao, L., Le Phung, M. L., & Tran, V. M. (2021). A Thompson sampling efficient multi-objective optimization algorithm (TSEMO) for lithium-ion battery liquid-cooled thermal management system: study of hydrodynamic, thermodynamic, and structural performance. ASME Journal of Electrochemical Energy Conversion and Storage, 18(2), 021009. (SCI)33. Liao, X., Ma, C., Peng, X., Li, Y., Duan, L., Garg, A., & Gao, L. (2021). A framework of optimal design of thermal management system for lithium-ion battery pack using multi-objectives optimization. ASME Journal of Electrochemical Energy Conversion and Storage, 18(2), 021005. (SCI)34. Li, F., Gao, L., Garg, A., Shen, W., & Huang, S. (2021). A comparative study of pre-screening strategies within a surrogate-assisted multi-objective algorithm framework for computationally expensive problems. Neural Computing and Applications, 33, 4387-4416. (SCI)35. Tan, W. J., Chin, C. M. M., Garg, A., & Gao, L. (2021). A hybrid disassembly framework for disassembly of electric vehicle batteries. International Journal of Energy Research, 45(5), 8073-8082. (SCI)36. Li, W., Garg, A., Xiao, M., & Gao, L. (2021). Optimization for liquid cooling cylindrical battery thermal management system based on Gaussian process model. Journal of Thermal Science and Engineering Applications, 13(2), 021015. (SCI)37. Vyas, M., Pareek, K., Spare, S., Garg, A., & Gao, L. (2021). State‐of‐charge prediction of lithium ion battery through multivariate adaptive recursive spline and principal component analysis. Energy Storage, 3(2), e147. (SCI)38. Ruhatiya, C., Gandra, R., Kondaiah, P., Manivas, K., Samhith, A., Gao, L., ... & Garg, A. (2021). Intelligent optimization of bioleaching process for waste lithium‐ion batteries: An application of support vector regression approach. International Journal of Energy Research, 45(4), 6152-6162. (SCI)39. Van Duong, M., Van Tran, M., Garg, A., Van Nguyen, H., Huynh, T. T. K., & Phung Le, M. L. (2021). Machine learning approach in exploring the electrolyte additives effect on cycling performance of LiNi0. 5Mn1. 5O4 cathode and graphite anode‐based lithium‐ion cell. International Journal of Energy Research, 45(3), 4133-4144. (SCI)40. Kaur, K., Garg, A., Cui, X., Singh, S., & Panigrahi, B. K. (2021). Deep learning networks for capacity estimation for monitoring SOH of Li‐ion batteries for electric vehicles. International Journal of Energy Research, 45(2), 3113-3128. (SCI)41. Li, F., Gao, L., Garg, A., Shen, W., & Huang, S. (2021). Two infill criteria driven surrogate-assisted multi-objective evolutionary algorithms for computationally expensive problems with medium dimensions. Swarm and Evolutionary Computation, 60, 100774. (SCI)42. Karthik, A., Kalita, P., Garg, A., Gao, L., Chen, S., & Peng, X. (2021). A Novel MOGA approach for power saving strategy and optimization of maximum temperature and maximum pressure for liquid cooling type battery thermal management system. International Journal of Green Energy, 18(1), 80-89. (SCI)43. Peng, X., Li, Y., Yang, W., & Garg, A. (2021). Real-time SOC Estimation of the EKF and UKF Algorithms Under Different Working Conditions. ASME Journal of Electrochemical Energy Conversion and Storage, 1-29. (SCI)44. Li, Y., Garg, A., Shevya, S., Li, W., Gao, L., & Lee Lam, J. S. (2022). A hybrid convolutional neural network-long short term memory for discharge capacity estimation of lithium-ion batteries ASME Journal of Electrochemical Energy Conversion and Storage, 19(3), 030901. (SCI)45. Garg, A., Su, S., Li, F., & Gao, L. (2020). Framework of model selection criteria approximated genetic programming for optimization function for renewable energy systems. Swarm and Evolutionary Computation, 59, 100750. (SCI)46. Garg, A., Yun, L., Gao, L., & Putungan, D. B. (2020). Development of recycling strategy for large stacked systems: Experimental and machine learning approach to form reuse battery packs for secondary applications. Journal of Cleaner Production, 275, 124152. (SCI)47. Li, W., Garg, A., Xiao, M., Peng, X., Le Phung, M. L., Tran, V. M., & Gao, L. (2020). Intelligent optimization methodology of battery pack for electric vehicles: A multidisciplinary perspective. International Journal of Energy Research, 44(12), 9686-9706. (SCI)48. Garg, A., Singh, S., Li, W., Gao, L., Cui, X., Wang, C. T., ... & Rajasekar, N. (2020). Illustration of experimental, machine learning, and characterization methods for study of performance of Li‐ion batteries. International Journal of Energy Research, 44(12), 9513-9526. (SCI)49. Cheng, L., Garg, A., Jishnu, A. K., & Gao, L. (2020). Surrogate based multi-objective design optimization of lithium-ion battery air-cooled system in electric vehicles. Journal of Energy Storage, 31, 101645. (SCI)50. Cui, X., Garg, A., Trang Thao, N., & Trung, N. T. (2020). Machine learning approach for solving inconsistency problems of Li‐ion batteries during the manufacturing stage. International Journal of Energy Research, 44(11), 9194-9204. (SCI)51. Sarmah, S. B., Kalita, P., Das, B., Garg, A., Gao, L., Pai, R. K., & Sarma, M. (2020). Numerical and experimental investigation of state of health of Li-ion battery. International Journal of Green Energy, 17(8), 510-520. (SCI)52. Peng, X., Cui, X., Liao, X., & Garg, A. (2020). A thermal investigation and optimization of an air-cooled lithium-ion battery pack. Energies, 13(11), 2956. (SCI)53. Vo, D. T., Phan, A. L. B., Tran, T. B., Nguyen, V. H., Le, T. M. L., Garg, A., ... & Le, P. M. L. (2020). Physicochemical and electrochemical properties of sulfolane–Carbonate electrolytes for sodium-ion conduction. Journal of Molecular Liquids, 307, 112982. (SCI)54. Li, W., Jishnu, A. K., Garg, A., Xiao, M., Peng, X., & Gao, L. (2020). Heat transfer efficiency enhancement of lithium-ion battery packs by using novel design of herringbone fins. ASME Journal of Electrochemical Energy Conversion and Storage, 17(2), 021108. (SCI)55. Chen, S., Bao, N., Peng, X., Garg, A., & Chen, Z. (2020). A thermal design and experimental investigation for the fast charging process of a lithium-ion battery module with liquid cooling. ASME Journal of Electrochemical Energy Conversion and Storage, 17(2), 021109.(SCI)Garg, A., Ruhatiya, C., Cui, X., Peng, X., Bhalerao, Y., & Gao, L. (2020). A novel approach for enhancing thermal performance of battery modules based on finite element modeling and predictive modeling mechanism. ASME Journal of Electrochemical Energy Conversion and Storage, 17(2), 021103. (SCI)56. Srinivaas, S., Li, W., Garg, A., Peng, X., & Gao, L. (2020). Battery thermal management system design: role of influence of nanofluids, flow directions, and channels. ASME Journal of Electrochemical Energy Conversion and Storage, 17(2), 021110. (SCI)57. Chen, S., Bao, N., Gao, L., Peng, X., & Garg, A. (2020). An experimental investigation of liquid cooling scheduling for a battery module. International Journal of Energy Research, 44(4), 3020-3032. (SCI)58. Garg, A., Shaosen, S., Gao, L., Peng, X., & Baredar, P. (2020). Aging model development based on multidisciplinary parameters for lithium‐ion batteries. International Journal of Energy Research, 44(4), 2801-2818. (SCI)59. Li, W., Garg, A., Le, M. L. P., Ruhatiya, C., & Gao, L. (2020). Electrochemical performance investigation of LiFePO4/C0. 15-x (x= 0.05, 0.1, 0.15 CNTs) electrodes at various calcination temperatures: Experimental and Intelligent Modelling approach. Electrochimica Acta, 330, 135314. (SCI)60. Nihanth, M. S. S., Ram, J. P., Pillai, D. S., Ghias, A. M., Garg, A., & Rajasekar, N. (2019). Enhanced power production in PV arrays using a new skyscraper puzzle based one-time reconfiguration procedure under partial shade conditions (PSCs). Solar Energy, 194, 209-224. (SCI)61. Vyas, M., Jain, M., Pareek, K., & Garg, A. (2019). Multivariate optimization for maximum capacity of lead acid battery through Taguchi method. Measurement, 148, 106904. (SCI)62. Garg, A., Wei, L., Goyal, A., Cui, X., & Gao, L. (2019). Evaluation of batteries residual energy for battery pack recycling: Proposition of stack stress-coupled-AI approach. Journal of Energy Storage, 26, 101001. (SCI)63. Sarmah, S. B., Kalita, P., Garg, A., Niu, X. D., Zhang, X. W., Peng, X., & Bhattacharjee, D. (2019). A review of state of health estimation of energy storage systems: Challenges and possible solutions for futuristic applications of li-ion battery packs in electric vehicles. ASME Journal of Electrochemical Energy Conversion and Storage, 16(4), 040801. (SCI)64. Liao, X., Ma, C., Peng, X., Garg, A., & Bao, N. (2019). Temperature distribution optimization of an air-cooling lithium-ion battery pack in electric vehicles based on the response surface method. ASME Journal of Electrochemical Energy Conversion and Storage, 16(4), 041002. (SCI)65. Wang, K., Li, X., Gao, L., & Garg, A. (2019). Partial disassembly line balancing for energy consumption and profit under uncertainty. Robotics and Computer-Integrated Manufacturing, 59, 235-251. (SCI)66. Singh, S., Srinivasan, K., Chen, B. Y., Singh, H., Goyal, A., Garg, A., & Cui, X. (2019). A novel method for determination of a time period for stabilization of power generation of microbial fuel cell with effect of microorganisms. International Journal of Energy Research, 43(11), 5834-5840. (SCI)67. Shaosen, S., Chen, D., Srinivasan, K., Chen, B. Y., Meijuan, X., Garg, A., ... & Sandoval, J. (2019). Experimental and artificial intelligence for determination of stable criteria in cyclic voltammetric process of medicinal herbs for biofuel cells. International Journal of Energy Research, 43(11), 5983-5991. (SCI)68. Goyal, A., Niu, X., Pham Le, N. P., Le Huynh, N. T., Tran, V. M., Phung Le, M. L., ... & Garg, A. (2019). Precision manufacturing of NaNi 1/3 Mn 1/3 co 1/3 O 2 cathodes: study of structure evolution and performance at varied calcination temperatures. Journal of Electronic Materials, 48, 5301-5309. (SCI)69. Li, W., Chen, S., Peng, X., Xiao, M., Gao, L., Garg, A., & Bao, N. (2019). A comprehensive approach for the clustering of similar-performance cells for the design of a lithium-ion battery module for electric vehicles. Engineering, 5(4), 795-802. (SCI)70. Vijayaraghavan, V., Garg, A., & Gao, L. (2019). Multiphysics-Based Statistical Model for Investigating the Mechanics of Carbon Nanotubes Membranes for Proton-Exchange Membrane Fuel Cell Applications. ASME Journal of Electrochemical Energy Conversion and Storage, 16(3), 031005. (SCI)71. Garg, A., Yun, L., Shaosen, S., Goyal, A., Niu, X., Gao, L., ... & Panda, B. (2019). A combined experimental‐numerical framework for residual energy determination in spent lithium‐ion battery packs. International Journal of Energy Research, 43(9), 4390-4402. (SCI)72. Li, W., Peng, X., Xiao, M., Garg, A., & Gao, L. (2019). Multi‐objective design optimization for mini‐channel cooling battery thermal management system in an electric vehicle. International Journal of Energy Research, 43(8), 3668-3680. (SCI)73. Chen, S., Peng, X., Bao, N., & Garg, A. (2019). A comprehensive analysis and optimization process for an integrated liquid cooling plate for a prismatic lithium-ion battery module. Applied Thermal Engineering, 156, 324-339. (SCI)74. Niu, X., Garg, A., Goyal, A., Simeone, A., Bao, N., Zhang, J., & Peng, X. (2019). A coupled electrochemical-mechanical performance evaluation for safety design of lithium-ion batteries in electric vehicles: An integrated cell and system level approach. Journal of Cleaner Production, 222, 633-645. (SCI)75. Peng, X., Chen, S., Garg, A., Bao, N., & Panda, B. (2019). A review of the estimation and heating methods for lithium‐ion batteries pack at the cold environment. Energy Science & Engineering, 7(3), 645-662. (SCI)76. Peng, X., Ma, C., Garg, A., Bao, N., & Liao, X. (2019). Thermal performance investigation of an air-cooled lithium-ion battery pack considering the inconsistency of battery cells. Applied Thermal Engineering, 153, 596-603. (SCI)77. Yun, L., Goyal, A., Singh, V. P., Gao, L., Peng, X., Niu, X., ... & Garg, A. (2019). Experimental coupled predictive modelling based recycling of waste printed circuit boards for maximum extraction of copper. Journal of cleaner production, 218, 763-771. (SCI)78. Yun, L., Li, W., Garg, A., Maddila, S., Gao, L., Fan, Z., ... & Wang, C. T. (2019). Maximization of extraction of Cadmium and Zinc during recycling of spent battery mix: An application of combined genetic programming and simulated annealing approach. Journal of Cleaner Production, 218, 130-140. (SCI)79. Yun, L., Sandoval, J., Zhang, J., Gao, L., Garg, A., & Wang, C. T. (2019). Lithium-ion battery packs formation with improved electrochemical performance for electric vehicles: experimental and clustering analysis. ASME Journal of Electrochemical Energy Conversion and Storage, 16(2), 021011. (SCI)80. Chen, D., Singh, S., Gao, L., Garg, A., Fan, Z., & Wang, C. T. (2019). A coupled and interactive influence of operational parameters for optimizing power output of cleaner energy production systems under uncertain conditions. International Journal of Energy Research, 43(3), 1294-1302. (SCI)81. Shui, L., Peng, X., Zhang, J., Garg, A., Nguyen, H. D., & Phung Le, M. L. (2019). A coupled mechanical–electrochemical study of Li-Ion battery based on genetic programming and experimental validation. ASME Journal of Electrochemical Energy Conversion and Storage, 16(1), 011008. (SCI)82. Li, W., Xiao, M., Peng, X., Garg, A., & Gao, L. (2019). A surrogate thermal modeling and parametric optimization of battery pack with air cooling for EVs. Applied Thermal Engineering, 147, 90-100. (SCI)83. Vijayaraghavan, V., Shui, L., Garg, A., Peng, X., & Singh, V. P. (2019). Crash analysis of lithium-ion batteries using finite element based neural search analytical models. Engineering with Computers, 35, 115-125. (SCI)84. Vijayaraghavan, V., Garg, A., & Gao, L. (2019). Multiphysics-Based Statistical Model for Investigating the Mechanics of Carbon Nanotubes Membranes for Proton-Exchange Membrane Fuel Cell Applications. ASME Journal of Electrochemical Energy Conversion and Storage, 16(3), 031005. (SCI)85. Le, L. T., Vo, T. D., Ngo, K. H., Okada, S., Alloin, F., Garg, A., & Le, P. M. (2018). Mixing ionic liquids and ethylene carbonate as safe electrolytes for lithium-ion batteries. Journal of Molecular Liquids, 271, 769-777. (SCI)86. Liang, X., Bao, N., Zhang, J., Garg, A., & Wang, S. (2018). Evaluation of battery modules state for electric vehicle using artificial neural network and experimental validation. Energy Science & Engineering, 6(5), 397-407. (SCI)87. Yun, L., Linh, D., Shui, L., Peng, X., Garg, A., Le, M. L. P., ... & Sandoval, J. (2018). Metallurgical and mechanical methods for recycling of lithium-ion battery pack for electric vehicles. Resources, Conservation and Recycling, 136, 198-208. (SCI)88. Huang, Y., Tran, B. T., Asghari, S., Nguyen, H. D., Peng, X., Garg, A., & Phung LE, M. L. (2018). Experimental and optimization of material synthesis process parameters for improving capacity of lithium‐ion battery. International Journal of Energy Research, 42(10), 3400-3409. (SCI)89. Huang, Y., Shui, L., Asghari, S., Prapainainar, P., Garg, A., & Kalita, P. (2018). A novel comprehensive procedure for determination of optimum operating conditions for cleaner energy production system. International Journal of Energy Research, 42(10), 3339-3350. (SCI)90. Zhang, J., Li, B., Garg, A., & Liu, Y. (2018). A generic framework for recycling of battery module for electric vehicle by combining the mechanical and chemical procedures. International Journal of Energy Research, 42(10), 3390-3399. (SCI)91. Nguyen, V. H., Huynh, L. T. N., Nguyen, T. H., Vu, T. P., Le, M. L. P., Grag, A., & Tran, V. M. (2018). Promising electrode material using Ni-doped layered manganese dioxide for sodium-ion batteries. Journal of Applied Electrochemistry, 48, 793-800. (SCI)92. Shui, L., Chen, F., Garg, A., Peng, X., Bao, N., & Zhang, J. (2018). Design optimization of battery pack enclosure for electric vehicle. Structural and Multidisciplinary Optimization, 58, 331-347. (SCI)93. Garg, A., Peng, X., Le, M. L. P., Pareek, K., & Chin, C. M. M. (2018). Design and analysis of capacity models for Lithium-ion battery. Measurement, 120, 114-120. (SCI)94. Rajan, A., Garg, A., Vijayaraghavan, V., Kuang, Y. C., & Ooi, M. P. L. (2018). Parameter optimization of polymer electrolyte membrane fuel cell using moment-based uncertainty evaluation technique. Journal of Energy Storage, 15, 8-16. (SCI)95. Rajan, A., Vijayaraghavan, V., Ooi, M. P. L., Garg, A., & Kuang, Y. C. (2018). A simulation-based probabilistic framework for lithium-ion battery modelling. Measurement, 115, 87-94. (SCI)96. Liao, W., Garg, A., & Gao, L. (2018). Design of robust energy consumption model for manufacturing process considering uncertainties. Journal of Cleaner Production, 172, 119-132. (SCI)97. Huang, Y., Garg, A., Asghari, S., Peng, X., & Le, M. L. P. (2018). Robust model for optimization of forming process for metallic bipolar plates of cleaner energy production system. International Journal of Hydrogen Energy, 43(1), 341-353. (SCI)98. Huang, Y., Gao, L., Yi, Z., Tai, K., Kalita, P., Prapainainar, P., & Garg, A. (2018). An application of evolutionary system identification algorithm in modelling of energy production system. Measurement, 114, 122-131. (SCI)99. Vijayaraghavan, V., Garg, A., & Gao, L. (2018). Fracture mechanics modelling of lithium-ion batteries under pinch torsion test. Measurement, 114, 382-389. (SCI)100. Garg, A., Vijayaraghavan, V., Zhang, J., & Lam, J. S. L. (2017). Robust model design for evaluation of power characteristics of the cleaner energy system. Renewable Energy, 112, 302-313. (SCI)101. Zhang, J., Xue, G., Du, H., Garg, A., Peng, Q., & Gu, P. (2017). Enhancing interface adaptability of open architecture products. Research in Engineering Design, 28, 545-560. (SCI)102. Garg, A., & Lam, J. S. L. (2017). Design of explicit models for estimating efficiency characteristics of microbial fuel cells. Energy, 134, 136-156. (SCI)103. Garg, A., Vijayaraghavan, V., Zhang, J., Li, S., & Liang, X. (2017). Design of robust battery capacity model for electric vehicle by incorporation of uncertainties. International Journal of Energy Research, 41(10), 1436-1451. (SCI)104. Jiang, D., Gong, J., & Garg, A. (2017). Design of early warning model based on time series data for production safety. Measurement, 101, 62-71. (SCI)105. Garg, A., Panda, B. N., & Lam, J. S. L. (2016). Functional characterization of current characteristic of direct methanol fuel cell. Fuel, 183, 432-440. (SCI)106. Garg, A., Lam, J. S. L., & Gao, L. (2016). Power consumption and tool life models for the production process. Journal of cleaner production, 131, 754-764. (SCI)107. Garg, A., Panda, B. N., Zhao, D. Y., & Tai, K. (2016). Framework based on number of basis functions complexity measure in investigation of the power characteristics of direct methanol fuel cell. Chemometrics and Intelligent Laboratory Systems, 155, 7-18. (SCI)108. Li, F., Gao, L., Garg, A., Shen, W., & Huang, S. (2021). Two infill criteria driven surrogate-assisted multi-objective evolutionary algorithms for computationally expensive problems with medium dimensions. Swarm and Evolutionary Computation, 60, 100774. (SCI)109. Garg, A., Vijayaraghavan, V., Mahapatra, S. S., Tai, K., & Wong, C. H. (2014). Performance evaluation of microbial fuel cell by artificial intelligence methods. Expert systems with applications, 41(4), 1389-1399. (SCI)110. Gao, L., & Garg, A. (Eds.). (2021). Special Section on Degradation Prediction and Recycling of Renewable Energy and Energy Storage Systems: Scenarios of 2020–2025. ASME Journal of Electrochemical Energy Conversion and Storage, 18(3), 030301. (SCI)