| Current trends for state-of-charge (SoC) estimation in lithium-ion battery electric vehicles IB Espedal, A Jinasena, OS Burheim, JJ Lamb Energies 14 (11), 3284, 2021 | 100 | 2021 |
| A Flexible Model for Benchmarking the Energy Usage of Automotive Lithium-Ion Battery Cell Manufacturing A Jinasena, OS Burheim, AH Strømman Batteries 7 (1), 14, 2021 | 47 | 2021 |
| Online Internal Temperature Sensors in Lithium-Ion Batteries: State-of-the-art and Future Trends A Jinasena, L Spitthoff, MS Wahl, JJ Lamb, P Shearing, AH Strømman, ... Frontiers in Chemical Engineering, 6, 2022 | 27 | 2022 |
| Extraction and degradation of chlorophyll a and b from Alternanthera sessilis MAM Jinasena, A Amarasinghe, B Amarasinghe, MAB Prashantha NSF: Colombo, 2016 | 24 | 2016 |
| The importance of optical fibres for internal temperature sensing in lithium-ion batteries during operation MS Wahl, L Spitthoff, HI Muri, A Jinasena, OS Burheim, JJ Lamb Energies 14 (12), 3617, 2021 | 22 | 2021 |
| Use of Orthogonal Collocation Method for a Dynamic Model of the Flow in a Prismatic Open Channel: For Estimation Purposes A Jinasena, GO Kaasa, R Sharma Proceedings of the 58th Conference on Simulation and Modelling (SIMS 58 …, 2017 | 19 | 2017 |
| Improved real–time estimation of return flow rate of drilling fluids by model adaptation for friction parameter A Jinasena, GO Kaasa, R Sharma IEEE Sensors Journal 19 (20), 9314-9323, 2019 | 12 | 2019 |
| Dynamic Model of an Ammonia Synthesis Reactor Based on Open Information A Jinasena, B Lie, B Glemmestad 9th EUROSIM Congress on Modelling and Simulation, 943-948, 2016 | 12 | 2016 |
| Study of an Industrial Electrode Dryer of a Lithium-Ion Battery Manufacturing Plant: Dynamic Modelling E Oppegård, A Jinasena, AH Strømman, JA Suul, OS Burheim Proceedings of the 61st Conference on Modelling and Simulation (SIMS 61) 176 …, 2020 | 10 | 2020 |
| Estimation of Mud Losses during the Removal of Drill Cuttings in Oil Drilling A Jinasena, R Sharma SPE Journal 25 (05), 2162-2177, 2020 | 9 | 2020 |
| Modeling and Analysis of Fluid Flow through A Non-Prismatic Open Channel with Application to Drilling A Jinasena, A Ghaderi, R Sharma Modeling, Identification and Control 39 (4), 261--272, 2018 | 9 | 2018 |
| A dynamic model for drain back to active mud pit combined with a well model during drilling I Pirir, A Jinasena, R Sharma Journal of Petroleum Science and Engineering 167, 803-818, 2018 | 6 | 2018 |
| A flexible model for benchmarking the energy usage of automotive lithium-ion battery cell manufacturing, Batteries 7 (2021) 14 A Jinasena, OS Burheim, AH Strømman | 6 | |
| Model based flow measurement using venturi umes for return flow during drilling I Pirir, A Jinasena, R Sharma | 5 | 2017 |
| Non-Newtonian Fluid Flow Measurement in Open Venturi Channel Using Shallow Neural Network Time Series and Non-Contact Level Measurement Radar Sensors NS Noori, TI Waag, H Viumdal, R Sharma, MH Jondahl, A Jinasena SPE Norway Subsurface Conference?, D011S001R003, 2020 | 4 | 2020 |
| Models and estimators for flow of topside drilling fluid A Jinasena University of South-Eastern Norway, 2019 | 4 | 2019 |
| Model based real–time flow rate estimation in open channels with application to conventional drilling A Jinasena, R Sharma 2018 18th International Conference on Control, Automation and Systems (ICCAS …, 2018 | 4 | 2018 |
| Current trends for state-of-charge (SoC) estimation in lithium-ion battery electric vehicles. Energies 2021; 14: 3284 IB Espedal, A Jinasena, OS Burheim, JJ Lamb | 4 | |
| Model Based Early Kick/Loss Detection and Attenuation with Topside Sensing in Managed Pressure Drilling A Jinasena, HHF Holta, MH Jondahl, PKW Welahettige, OM Aamo, ... Proceedings of the 61st Conference on Modelling and Simulation (SIMS 61) 176 …, 2020 | 2 | 2020 |
| Adaptive Moving Horizon Estimator for Return Flow Rate Estimation using Fluid Levels of a Venturi Channel A Jinasena, R Sharma Modeling, Identification and Control 41 (2), 79-90, 2020 | 2 | 2020 |
Odne Stokke BurheimProfessor at NTNU, Trondheim NorwayVerified email at ntnu.no
