| Remaining energy estimation for lithium-ion batteries via Gaussian mixture and Markov models for future load prediction M Faraji Niri, TMN Bui, TQ Dinh, E Hosseinzadeh, TF Yu, J Marco Journal of Energy Storage 28, 101271, 2020 | 67 | 2020 |
| State of power prediction for lithium-ion batteries in electric vehicles via wavelet-Markov load analysis MF Niri, TQ Dinh, TF Yu, J Marco, TMN Bui IEEE Transactions on Intelligent Transportation Systems 22 (9), 5833-5848, 2020 | 48 | 2020 |
| Interpretable machine learning for battery capacities prediction and coating parameters analysis K Liu, MF Niri, G Apachitei, M Lain, D Greenwood, J Marco Control Engineering Practice 124, 105202, 2022 | 47 | 2022 |
| Quantifying key factors for optimised manufacturing of Li-ion battery anode and cathode via artificial intelligence MF Niri, K Liu, G Apachitei, LAA Román-Ramírez, M Lain, D Widanage, ... Energy and AI 7, 100129, 2022 | 44 | 2022 |
| Machine learning for optimised and clean Li-ion battery manufacturing: Revealing the dependency between electrode and cell characteristics MF Niri, K Liu, G Apachitei, LR Ramirez, M Lain, D Widanage, J Marco Journal of Cleaner Production 324, 129272, 2021 | 37 | 2021 |
| Accelerated state of health estimation of second life lithium-ion batteries via electrochemical impedance spectroscopy tests and machine learning techniques M Faraji-Niri, M Rashid, J Sansom, M Sheikh, D Widanage, J Marco Journal of Energy Storage 58, 106295, 2023 | 33 | 2023 |
| Stochastic stability and stabilization of a class of piecewise‐homogeneous Markov jump linear systems with mixed uncertainties M Faraji‐Niri, MR Jahed‐Motlagh, M Barkhordari‐Yazdi International Journal of Robust and Nonlinear Control 27 (6), 894-914, 2017 | 28 | 2017 |
| Roadmap on Li-ion battery manufacturing research PS Grant, D Greenwood, K Pardikar, R Smith, T Entwistle, LA Middlemiss, ... Journal of Physics: Energy 4 (4), 042006, 2022 | 27 | 2022 |
| Systematic analysis of the impact of slurry coating on manufacture of Li-ion battery electrodes via explainable machine learning MF Niri, C Reynolds, LAAR Ramírez, E Kendrick, J Marco Energy Storage Materials 51, 223-238, 2022 | 24 | 2022 |
| An Advanced Hardware-in-the-Loop Battery Simulation Platform for the Experimental Testing of Battery Management System TMN Bui, M Faraji Niri, D Worwood, TQ Dinh, J Marco 2019 23rd International Conference on Mechatronics Technology (ICMT), 1-6, 2019 | 22 | 2019 |
| Understanding the effect of coating-drying operating variables on electrode physical and electrochemical properties of lithium-ion batteries LA Román-Ramírez, G Apachitei, M Faraji-Niri, M Lain, WD Widanage, ... Journal of Power Sources 516, 230689, 2021 | 20 | 2021 |
| Stochastic stability and stabilization of Markov jump linear systems with instantly time-varying transition rates: A unified framework M Faraji-Niri, MR Jahed-Motlagh ISA transactions 65, 51-61, 2016 | 18 | 2016 |
| Effect of coating operating parameters on electrode physical characteristics and final electrochemical performance of lithium-ion batteries LA Román-Ramírez, G Apachitei, M Faraji-Niri, M Lain, D Widanage, ... International Journal of Energy and Environmental Engineering 13 (3), 943-953, 2022 | 12 | 2022 |
| Stochastic stability and stabilization of semi-Markov jump linear systems with uncertain transition rates M Faraji-Niri, MR Jahed-Motlagh Information Technology and Control 46 (1), 37-52, 2017 | 12 | 2017 |
| Stabilization of active fault‐tolerant control systems by uncertain nonhomogeneous markovian jump models M Faraji‐Niri, MR Jahed‐Motlagh, M Barkhordari‐Yazdi Complexity 21 (S1), 318-329, 2016 | 12 | 2016 |
| Machine Learning in Lithium‐Ion Battery Cell Production: A Comprehensive Mapping Study S Haghi, MFV Hidalgo, MF Niri, R Daub, J Marco Batteries & Supercaps, e202300046, 2023 | 10 | 2023 |
| Performance evaluation of convolutional auto encoders for the reconstruction of li-ion battery electrode microstructure M Faraji Niri, J Mafeni Mase, J Marco Energies 15 (12), 4489, 2022 | 10 | 2022 |
| Dataset for rapid state of health estimation of lithium batteries using EIS and machine learning: Training and validation M Rashid, M Faraji-Niri, J Sansom, M Sheikh, D Widanage, J Marco Data in Brief 48, 109157, 2023 | 8 | 2023 |
| Machine learning for investigating the relative importance of electrodes’ N: P areal capacity ratio in the manufacturing of lithium-ion battery cells MF Niri, G Apachitei, M Lain, M Copley, J Marco Journal of Power Sources 549, 232124, 2022 | 8 | 2022 |
| The Impact of Calendering Process Variables on the Impedance and Capacity Fade of Lithium‐Ion Cells: An Explainable Machine Learning Approach M Faraji Niri, G Apachitei, M Lain, M Copley, J Marco Energy Technology, 2200893, 2022 | 8 | 2022 |
James MarcoWarwick Universityایمیل تأیید شده در warwick.ac.uk
