Dr Anindita Roy is a renewable energy technologist, currently an associate professor in Mechanical Engineering Department at Symbiosis Institute of Technology, Pune. She is a doctorate from Department of Energy Science & Engineering at IIT Bombay and a masters in Energy Management from DAVV, Indore.
Her research interests are indigenization of small wind turbines, modeling and simulation of hybrid renewable Energy Systems, thermocline-based energy storage, O&M of lead acid battery-based systems, and fast charging solutions for electrical vehicles.
In her PhD, she worked on the optimal design of Isolated Wind-battery Power Systems. She has authored a Book with Springer Nature on ‘Wind Power Based Isolated Energy Systems’
She was instrumental in setting up the “Battery and Solar Energy laboratory “at PCCoE which offers training, testing and consultancy services in Collaboration with Customized Energy Solutions (CES).
She is a LIFE member of SESI, Institution of Engineers India (IEI) and
Renewable Energy Integration
Modelling and simulation of renewable energy systems
Fast charging of lead acid batteries
49
Scopus Publications
687
Scholar Citations
12
Scholar h-index
17
Scholar i10-index
Scopus Publications
Artificial intelligence driven sustainability in tomato supply chains optimization a systematic review Shivali Amit Wagle, Kunal Kulkarni, Sreelekha Arun, Anindita Roy, Choon Kit Chan, Subhav Singh, Deekshant Varshney Discover Sustainability, 2026 Agricultural supply chains are crucial to ensuring that the world’s food demand is met effectively but also sustainably. This paper focuses on the Supply Chain Management (SCM) in agriculture with particular reference to perishable commodities such as tomatoes. The characteristics of tomatoes such as their short shelf life, vulnerability to environmental factors and poor stakeholder networks present a major challenge to production, post-harvest handling, transportation, and market distribution. The advent of Artificial Intelligence (AI) and Machine Learning (ML) have emerged as promising tools to address these challenges through data-driven decision-making, automation, and predictive analytics. A total of 116 studies were referred and synthesized based on a multi-stage title, abstract, and full-text selection process, which used Web of Science, Scopus, IEEE Xplore, and ScienceDirect, combining qualitative thematic evaluation with quantitative bibliometric analysis. The review synthesizes AI/ML applications across agricultural SCM and key stages of the tomato supply chain, including smart farming, post-harvest quality assessment, cold-chain logistics, distribution, and consumer-level traceability. AI/ML methods can optimize operations like smart farming, post-harvest quality assessment, logistics optimization, and market forecasting. These applications contribute to sustainability by reducing food waste, improving resource efficiency, lowering emissions, and enhancing farmer livelihoods. With the focus of sustainability, this study provides insights for advance tomato supply chains using AI-driven technologies.
Optimal design of phase change material integrated cold rooms for sustainable cold-chain management A Sreelekha, Stefano Landini, Anindita Roy Energy Conversion and Management, 2026 • Developed generalized PCM-VCR cold storage design space and sizing methodology. • Combined time-series simulation, optimization, and experimental validation. • Enabled quick identification of efficient system configs minimizing energy cost. • Demonstrated intermittent vs continuous PCM discharge for thermal backup. • Supports sustainable cold chain with energy savings and cost-effectiveness. Decentralized micro-cold storages (less than 5 metric tonnes of storage capacity) operating on vapor compression refrigeration (VCR) represent a key element in food preservation supply chain. Integration of thermal storage in cold room benefits from reduced temperature fluctuations along with reduction in compressor running time leading to energy savings. However, the energy consumed in charging the thermal storage is closely connected to the size (mass) of the phase change material (PCM) which is often overlooked. In this study, we propose a mathematical framework for sizing and optimization of the thermal storage unit through a systematic timestep simulation of energy balance of the entire system over a specified time horizon of operation. Inputs to the model are the ambient temperature and thermal load on the cold room along with the equipment characteristics. The design space is a graphical representation of all feasible design solutions on an evaporator area vs compressor power rating diagram with PCM mass as a variable. The key contribution of this work lies in identifying the feasible combinations and limiting values of the system design variables that enables a quick selection of an optimum configuration based on desired objective. Minimization of levelized cost of storage (LCOS) was chosen as the optimization objective. The optimum configuration for a 6-hour uninterrupted thermal backup capable of storing 0.5 ton of produce comprise of a compressor rated power of 800 W with 3.8 m 2 evaporator area and 142 kg of PCM for leading to a LCOS of US$ 0.47/ kWh.
Investigation on PCM-Based cold storage performance under variable charging temperatures and layout configurations Raju Yenare, Chandrakant Sonawane, Hitesh Navinchandra Panchal, Arunkumar Bongale, Anindita Roy, Nithesh Naik, Choon Kit Chan, Saurav Dixit, Subhav Singh Energy Conversion and Management X, 2026 • Experimental study of PCM layout and charging temperature effects. • Layout 3 achieves 11.5 h cooling and 82.3% effectiveness. • Energy-normalized performance reaches 4.2 h/kWh. • Heat transfer coefficients quantified (h up to 8.7 W/m 2 °C). • Optimized PCM layout improves cooling efficiency significantly. Efficient thermal management in passive refrigeration systems is essential for preserving temperature-sensitive products during transport and storage. Phase Change Materials (PCMs) have emerged as promising candidates for enhancing the thermal buffering capacity of portable cold storage units due to their latent heat storage capabilities. This study investigates the thermal performance of a PCM-based cold storage system using RT4 paraffin wax as the energy storage medium, with a focus on both charging and discharging behavior. The primary objective is to evaluate the influence of PCM layout configurations and charging temperatures (–5 °C, –10 °C, and –15 °C) on system cooling performance under realistic operating conditions. Three different PCM layouts—top (Layout 1), bottom (Layout 2), and all four sides (Layout 3)—were experimentally analyzed inside a temperature-controlled chamber using calibrated thermocouples to monitor PCM and air temperatures throughout the thermal cycles. Experimental results showed that Layout 3 delivered the most uniform and extended cooling during the discharging phase, maintaining cabin air below 8 °C for approximately 6 h at a charging temperature of − 15 °C. Lower charging temperatures significantly improved latent heat utilization, enhanced PCM solidification, and increased the holdover duration by up to 35% compared to − 5 °C. In contrast, Layouts 1 and 2 exhibited directional cooling inefficiencies and quicker temperature rise due to suboptimal heat absorption. The results underscore the importance of PCM spatial configuration and pre-charging conditions in achieving effective thermal management. A combined uncertainty of ± 0.64 °C confirmed the robustness and reliability of the experimental setup and measurements. The results establish a quantitative understanding of the transient thermal response of three PCM layout configurations and uncover the coupled regulation mechanism between charging temperature and PCM placement, demonstrating how buoyancy-driven natural convection governs heat transfer pathways and latent heat utilization in compact PCM-based cold storage systems.
Reliability analysis of heating ventilation and air-conditioning (HVAC) system of passenger cars using field failure data Arya Pramod Gokhale, Anuj Sureshkumar Mishra, Ayush Ishwarchandra Jaiswal, Akshay Naresh Sawant, Rajkumar Bhimgonda Patil, Hari Vasudevan, Pravin Hindurao Yadav, Anindita Roy, Choon Kit Chan, Deekshant Varshney, Subhav Singh Results in Engineering, 2026 • Geographical disparity in HVAC failures analyzed using field data across India. • Pareto analysis and probability modeling identify key high-failure zones. • Extreme climates and pollution linked to frequent refrigerant and blower issues. This study presents a comprehensive reliability analysis of Heating, Ventilation, and Air Conditioning (HVAC) systems in passenger cars, utilizing large-scale field failure data segmented by region, zone, and area across India. A methodology is proposed that identifies outliers from the field failure data and employs Pareto analysis, statistical modeling, and reliability analysis to identify high-risk segments and inform targeted design and maintenance interventions, as well as design improvements. The Pareto and reliability study shows that approximately 80% of HVAC failures are concentrated in just a few regions, namely Delhi, Uttar Pradesh, Maharashtra, and Gujarat, which contribute the highest number of failure incidents. The subsystems/ components, such as blower assemblies and refrigerant lines, are the primary contributors to system failures. The study established the Weibull 2/3 parameter model as the best fit for failure prediction across most geographies. These findings underscore the crucial need for region-specific maintenance strategies and targeted design enhancements, such as improved motor bearings and enhanced sealing, to minimize downtime and prolong HVAC lifespan in high-failure areas. The study demonstrates the value of using real-world operational data to inform predictive maintenance and optimise HVAC reliability across geographically diverse conditions.
Experimental Data-Driven Machine Learning Analysis for Prediction of PCM Charging and Discharging Behavior in Portable Cold Storage Systems Raju R. Yenare, Chandrakant Sonawane, Anindita Roy, Stefano Landini Sustainability Switzerland, 2026 The problem of the post-harvest loss of perishable products has been a loss facing food security, especially in areas that lack adequate cold chain facilities. This issue is directly connected with sustainability objectives because post-harvest losses are the major source of food wastage, unneeded energy use, and related greenhouse gas emissions. Cold storage with phase-change material (PCM) is a promising alternative, as it aims at stabilizing temperatures and enhancing energy consumption, but current analyses of performance have been conducted through experimental testing and computational fluid dynamic (CFD) simulations, which are precise but computationally expensive. To handle this drawback, the current work constructs a machine learning predictive model to predict the dynamics of charging and discharging temperature of PCM cold storage systems. Four regression models, namely Random Forest, Extreme Gradient Boosting (XGBoost), Support Vector Regression (SVR), and K-Nearest Neighbors (KNNs), were trained and tested on experimental datasets that were obtained for varying storage layouts. The various error and accuracy measures used to determine model performance comprised MSE, MAE, R2, MAPE, and percentage accuracy. The findings suggest that Random Forest provides the best accuracy during both the charging and the discharging process, with the highest R2 values of over 0.98 and with minimal mean absolute errors. The KNN model was competitive in the discharge process, especially in cases of consistent thermal recovery patterns, and XGBoost was consistent in layout accuracy. However, SVR had relatively lower robustness, particularly when using nonlinear charged dynamics. Among the evaluated models, the Random Forest algorithm demonstrated the highest predictive accuracy, achieving coefficients of determination (R2) exceeding 0.98 for both charging and discharging processes, with mean absolute errors below 0.6 °C during charging and 0.3 °C during discharging. This paper has proven that machine learning is an efficient surrogate to CFD and experimental-only methods and can be used to predict the thermal behavior of PCM quickly and precisely. The proposed framework will allow for developing cold storage systems based on energy efficiency, low costs, and sustainability, especially in the context of decentralized and resource-limited agricultural supply chains, with the help of quick and data-focused forecasting of PCM thermal behavior.
A bibliometric review of hydrogen fuel cell research: trends in safety, reliability, and performance analysis (2020–2024) Ashwini Gotmare, Rajkumar Bhimgonda Patil, Atul Dhale, Hari Vasudevan, Sameer Al-Dahidi, Anindita Roy International Journal of Sustainable Energy, 2026 With increasing global attention on sustainable energy solutions, hydrogen Fuel Cells (FCs) have gained prominence as a viable technology for addressing environmental concerns. Despite increasing research, a systematic bibliometric analysis focusing on the safety, reliability, and performance of these methods remains limited. This gap restricts the ability of regulators and risk–assessment communities to identify critical risks and research priorities. This study presents a comprehensive bibliometric analysis to map the global research landscape on hydrogen FC technologies from 2020 to 2024. Scopus-indexed data is used to get citation metrics and VOSviewer-based network visualizations. A detailed assessment of publication trends, author collaborations, and thematic developments is carried out. Results indicate a significant increase in research activity, with 18,722 publications generating 380,174 citations. China, India, and the United States lead in publication volume, while Switzerland and Sweden show the highest citation impact per paper. The Dominant research themes include FC performance, hydrogen production, and emerging areas, such as microbial FCs and hydrogen storage. The study provides valuable insights for researchers, institutions, and policymakers, supporting informed decisions in journal selection, funding allocation, and strategic research planning. The need for interdisciplinary collaboration and real-world data integration is emphasised with recommendations on future research focused on commercialization, policy alignment, and expanding application domains.
Analysis of Energy Conservation Measures using Calibrated Building Energy Simulation Model , Arvind Kumar Prajapat, Akshay Pahade, , Kiran Giri, , Anindita Roy, , Mugdha Kshirsagar, , Rita S Pimpalkar, and Es Energy and Environment, 2025 Building Energy Modelling (BEM) is a tool used for green certification, code compliance, real-time building control, and utility incentives.Applying energy conservation measures can result in a large reduction in a building's annual energy use.This research aims to investigate how different Energy Conservation Measures (ECMs) affect a commercial building's energy usage.For this eQUEST 3.65, a building energy modelling and simulation tool is used for estimating energy use.The BES model on eQUEST was calibrated using electricity bills to provide reliable results and simulated forecasts that are similar to real-world energy use.The model was calibrated by calculating three statistical indices:The ASHRAE guideline 14 limits are contrasted with the Mean Bias Error (MBE), the Coefficient of Variation of the RMSE (Cv (RMSE), and the Coefficient of determination (R2).Four different ECMs: adding insulation, employing LED lighting, applying glass coating and combined ECM were identified after analysing the end-use energy consumption.It was found therefrom that application of the above measures resulted in 0.6 %, 8.5 %, 13.6%, and 26.1% savings in the building's annual energy consumption.Thus, the combined ECM strategy proved to be the most beneficial.Energy simulations are thus a valuable tool for achieving the overall sustainability of buildings.
Numerical Investigation of Hybrid Immersion Cooling Strategies for Battery Packs in Light Electric Vehicles Stefano Landini, Jack Panter, Anindita Roy, Gordhan Das Valasai, Mohammad Fawzi Ismail Journal of Fluid Flow Heat and Mass Transfer, 2025 This work investigates a new hybrid thermal management system (TMS) for light electric vehicle (LEV) battery packs that uses dielectric liquid immersion cooling, heat pipes and fins to effectively control lithium-ion battery (LIB) thermal load.Different commercial dielectric oil chemistries (Cargill DE-11772 and EF-3221, LK-STO50, and MIVOLT-DFK) are evaluated as heat transfer fluids (HTFs) and compared with air and deionised water as benchmark.Additionally, the effects of heat pipe diameters (4 mm, 6 mm, and 8 mm) and the number of fins (1, 2, 3, and 5) are analysed for two configurations: fins evenly distributed along the heat pipe and fins placed only on the upper half.A 3D steady-state CFD model is developed in Ansys 2024R2 to simulate the proposed TMS for a 4S4P (14.8V, 10 Ah) Lithium-Nickel Manganese Cobalt (NMC) battery pack.Under typical 2C discharge rate, the model examines the TMS thermal performance when simulating heat transfer with and without buoyancy effects.Buoyancy improves cooling performance, especially for viscous fluids, lowering battery, HTF, and heat sink temperatures by 20%.With modest LIB heat generation rates (up to 25 kW/m), the TMS ensures effective cooling with minimum temperature increase.However, when reaching heat generation rates up to 100 kW/m, the battery temperature reaches 91.13C, revealing the system's cooling capability limitations.The study examines the effect of changing heat sink and insulation equivalent convective heat transfer coefficients.Increasing the heat sink coefficient from 10 to 100 W/mK lowers the battery temperature from 138C to 49C, while increasing the insulation equivalent heat transfer coefficient from 1 to 50 W/mK lowers battery temperature from 92C to 46C.Also, the effect of heat pipes diameter and fins number and vertical distribution is analysed, pointing to the design with 5 evenly distributed fins to be the best thermally performing while limiting additional TMS mass.This study shows that the hybrid TMS using heat pipes, fins, immersion cooling improves compact LEV safety, performance, and battery longevity under high-demand situations.
A bibliometric review of hydrogen fuel cell research: trends in safety, reliability, and performance analysis (2020–2024) A Gotmare, RB Patil, A Dhale, H Vasudevan, S Al-Dahidi, A Roy International Journal of Sustainable Energy 45 (1), 2637991 , 2026 2026 Citations: 1
Optimal design of phase change material integrated cold rooms for sustainable cold-chain management A Sreelekha, S Landini, A Roy Energy Conversion and Management 357, 121454 , 2026 2026
Artificial intelligence driven sustainability in tomato supply chains optimization a systematic review SA Wagle, K Kulkarni, S Arun, A Roy, CK Chan, S Singh, D Varshney Discover Sustainability , 2026 2026
Investigation on PCM-Based cold storage performance under variable charging temperatures and layout configurations R Yenare, S Chandrakant, H Panchal, A Bongale, A Roy, N Naik, ... Energy Conversion and Management: X, 101854 , 2026 2026
Real-time prediction of state of charge and state of health in lithium-ion battery systems using machine learning techniques K Garse, K Bairwa, R Mali, A Pandhare, A Roy, C Bhalerao AIP Conference Proceedings 3369 (1), 040037 , 2026 2026
Reliability analysis of heating ventilation and air-conditioning (HVAC) system of passenger cars using field failure data AP Gokhale, AS Mishra, AI Jaiswal, AN Sawant, RB Patil, H Vasudevan, ... Results in Engineering 29, 108819 , 2026 2026
Experimental Data-Driven Machine Learning Analysis for Prediction of PCM Charging and Discharging Behavior in Portable Cold Storage Systems RR Yenare, C Sonawane, A Roy, S Landini Sustainability 18 (3), 1467 , 2026 2026
Mathematical modelling and sizing of solar photovoltaic powered decentralised cold room with hybrid storage system S Arun, A Roy, S Landini, A Pahade Shaping Tomorrow: Emerging Technologies for Sustainable Future, 1302 , 2025 2025
Analysis of Energy Conservation Measures using Calibrated Building Energy Simulation Model AK Prajapat, A Pahade, K Giri, A Roy, M Kshirsagar, RS Pimpalkar ES Energy and Environment 29, 1723 , 2025 2025 Citations: 1
Bibliometric Analysis of Hydrogen-Powered Vehicle Safety and Reliability Research: Trends, Impact, and Future Directions RB Patil, A Roy, S Al-Dahidi, S Mane, D Birajdar, R Chaurasia, S Auti Hydrogen 6 (2), 42 , 2025 2025
Numerical investigation of hybrid immersion cooling strategies for battery packs in light electric vehicles S Landini, J Panter, A Roy, GD Valasai, MF Ismail Journal of Fluid Flow, Heat and Mass Transfer 12, 242-250 , 2025 2025 Citations: 2
Strategies for Hybrid Immersion Cooling Of Light Electric Vehicle Battery Packs: A Numerical Investigation S Landini, A Roy, M Ismail, J Panter, GD Valasai Proceedings of the 10th World Congress on Momentum, Heat and Mass Transfer … , 2025 2025
Analysis of Thermal Aspect in Hard Turning of AISI 52100 Alloy Steel Under Minimal Cutting Fluid Environment Using FEM S Mane, RB Patil, ML Kolhe, A Roy, AG Kamble, A Chaudhari Applied Mechanics 6 (2), 26 , 2025 2025 Citations: 2
Wind Turbine Gearbox Fault Detection Based on Statistical Learning MF Khan, S Lohar, JH Jun, HS Dhiman, A Roy ES Energy and Environment 28, 1451 , 2025 2025
A smart solar PV monitoring system using internet of things (IoT) ASAR Rita Pimpalkar Concurrent Engineering: Research and Applications, 1-11 , 2025 2025 Citations: 2
Analysis of the surface quality characteristics in hard turning under a minimal cutting fluid environment S Mane, RB Patil, A Roy, P Shah, R Sekhar Applied Mechanics 6 (1), 5 , 2025 2025 Citations: 6
Optimizing micro cold storage for detecting stale food and fruits S Arun, SA Wagle, P Nambiar, P Panalkar, P Ekka, V Kumar, H Dhiman, ... Science and Technology for Energy Transition 80, 43 , 2025 2025 Citations: 1
Reliability analysis and life cycle costing of rooftop solar photovoltaic (PV) system operating in a composite environment R Pimpalkar, A Sahu, A Yadao, RB Patil, A Roy Science and Technology for Energy Transition 80, 32 , 2025 2025 Citations: 8
Cutting-edge approaches for customizing sulfur cathode materials in sodium–sulfur batteries operating at ambient temperature PS Khaire, D Kumar, K Mishra, A Roy Journal of Materials Chemistry A 13 (12), 8282-8314 , 2025 2025 Citations: 10
Application of the design space approach for optimal sizing and placement of distributed generation HP Pohankar, MS Thakare, A Roy International Journal of Ambient Energy 45 (1), 2434862 , 2024 2024
MOST CITED SCHOLAR PUBLICATIONS
Optimum sizing of wind-battery systems incorporating resource uncertainty A Roy, SB Kedare, S Bandyopadhyay Applied Energy 87 (8), 2712-2727 , 2010 2010 Citations: 177
Application of design space methodology for optimum sizing of wind–battery systems A Roy, SB Kedare, S Bandyopadhyay Applied Energy 86 (12), 2690-2703 , 2009 2009 Citations: 92
Design & optimization of a small wind turbine blade for operation at low wind speed AR Manoj kumar Chaudhary World Journal of Engineering 12 (1), 83-94 , 2015 2015 Citations: 73
A comprehensive review on failure modes and effect analysis of solar photovoltaic system R Pimpalkar, A Sahu, RB Patil, A Roy Materials Today: Proceedings 77, 687-691 , 2023 2023 Citations: 28
The effect of fast charging and equalization on the reliability and cycle life of the lead acid batteries A Roy, RB Patil, R Sen Journal of Energy Storage 55, 105841 , 2022 2022 Citations: 26
Wind power based isolated energy systems ARS Bandyopadhyay Springer, Switzerland , 2019 2019 Citations: 24
Analysis on the feasibility of a PV-diesel generator hybrid system without energy storage ARGN Kulkarni Clean technologies and energy policy , 2016 2016 Citations: 20
Evaluating energy-saving potential in micro-cold storage units integrated with phase change material AW A Roy, S Kale, AB Lingayat, A Sur, D Sengar, S Gawade Journal of the Brazilian Society of Mechanical Sciences and Engineering, 45 … , 2023 2023 Citations: 18
Life cycle testing and reliability analysis of prismatic lithium-iron-phosphate cells A Roy, S Meshram, RB Patil, S Arun, A Kore International Journal of Sustainable Energy 43 (1), 2337439 , 2024 2024 Citations: 16
Hybrid Random Forest Regression and Artificial Neural Networks for Modelling and Monitoring the State of Health of Li-Ion Battery AR Komal Mohan Garse, Kedar Narayan Bairwa Journal of Electrical Systems 20 (2) , 2024 2024 Citations: 14
Design and Optimization of Photovoltaic-Diesel Generator-Battery Hybrid System for off-grid areas AR Monika G Barade International Journal of Current Engineering and Technology , 2016 2016 Citations: 14
Challenges to diffusion of small wind turbines in India A Roy, A Rathod, GN Kulkarni 2nd IET Renewable Power Generation Conference (RPG 2013), 3. C34 , 2013 2013 Citations: 14
Numerical and experimental investigation on performance of thermal energy storage integrated micro-cold storage unit S Arun, RJ Boche, P Nambiar, P Ekka, P Panalkar, V Kumar, A Roy, ... Applied Sciences 14 (12), 5166 , 2024 2024 Citations: 12
PERFORMANCE ANALYSIS OF AN ENERGY EFFICIENT PCM-BASED ROOM COOLING SYSTEM AS A Roy, U Shaikh, S Kale Frontiers in Heat and Mass Transfer , 2023 2023 Citations: 12
Cutting-edge approaches for customizing sulfur cathode materials in sodium–sulfur batteries operating at ambient temperature PS Khaire, D Kumar, K Mishra, A Roy Journal of Materials Chemistry A 13 (12), 8282-8314 , 2025 2025 Citations: 10
Physical design space for isolated wind-battery system incorporating resource uncertainty A Roy, SB Kedare, S Bandyopadhyay Proceedings of the Institution of Mechanical Engineers, Part A: Journal of … , 2011 2011 Citations: 10
Design space for isolated power systems-a deterministic approach A Roy, P Arun, S Bandyopadhyay SESI Journal 17 (1), 54-69 , 2007 2007 Citations: 10
Investigating the reliability of heating, ventilation, and air conditioning systems utilized in passenger vehicles SK Kale, M Shelar, S Auti, PV Ingle, A Roy, CR Sonawane, RB Patil Applied Sciences 14 (22), 10522 , 2024 2024 Citations: 9
Design and optimization of renewable energy based isolated power systems A Roy, P Arun, S Bandyopadhyay SESI Journal 17 (1-2), 54-69 , 2007 2007 Citations: 9
Reliability analysis and life cycle costing of rooftop solar photovoltaic (PV) system operating in a composite environment R Pimpalkar, A Sahu, A Yadao, RB Patil, A Roy Science and Technology for Energy Transition 80, 32 , 2025 2025 Citations: 8
