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    Impact of magnetic fields on magnetic nanofluid heat transfer in enhanced mini-channels for high-performance cooling
    (Elsevier, 2025-12) Bhattacharyya, Suvanjan
    This study computationally compares various minichannel configurations to improve heat transfer efficiency and lower battery surface temperatures, ensuring safe operation and extended lifespan. Utilizing CuO/water, Fe3O4/ water and CuO + Fe3O4/ water as the coolant, the study incorporates passive methods to foil the boundary layer for eddy formation, alongside magnets to enhance eddy formation. The computational analysis evaluates heat transfer effectiveness using parameters such as the Nusselt number, friction factor, Colburn j-factor, and TEF. The velocity and the temperature profile has also been depicted to further strengthen the understanding of the fluid flow variations under the influence of magnets. The results show a 65.49 % increase in the Nusselt number compared to a plain channel with water, while the Colburn j-factor rises by 65.49 % for the CuO/ water nanofluid. Although the friction factor also sees a notable increase, the performance improving factor reaches a peak of 2 for Fe3O4/ water nanofluid. All these findings are taken at the Reynolds number of 250 when a couple of magnets are positioned at the distance of 0. 15 × 102 mm and 0. 25 × 102 mm from the entrance of the channel and the results obtained highlight the dominance of the staggered upstream ribbed configuration over other designs, making it a promising approach for cooling systems in EVs and HEVs.
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    Experimental and numerical investigation for optimization of a hybrid battery thermal management system based on phase change material and air convection
    (ASME, 2024-12) Verma, Saket
    This work presents the design and optimization of a phase change material (PCM)-based hybrid battery thermal management system (HBTMS). In the first stage, experiments are performed to measure the battery cell temperatures under various charge rates with and without the usage of PCM. Thereafter, a numerical model is developed to conduct a parametric study on the effect of the thickness of PCM layer around the battery cell. The results show that with the PCM thicknesses of 6–12 mm, the maximum cell temperature (36.35 °C) and thermal nonuniformity are within the safe range. In the second stage, a parametric study is conducted in the 6S1P battery module to optimize the spacing between the cells at constant inlet velocity. The result shows that an increase in cell spacing decreases the maximum temperature within the cells. The maximum temperature is within the optimal range when the cell spacing is 10 mm. At the constant cell spacing of 10 mm, an increase in inlet velocities from 0.25 m/s to 2.5 m/s gradually improves the thermal uniformity. The maximum temperature and thermal nonuniformity for the 6S1P battery module are found to be 42.07 °C and 1.17 °C respectively. In the third stage, the 6S1P battery module is optimized for PCM thickness, cell spacing, and inlet air velocity. It is found that effective thermal management is possible with PCM-based HBTMS at a low airflow rate of up to 1.5 m/s. The optimized PCM-based HBTMS shows 53.95% and 40% reductions in PCM mass and air flowrate, respectively.
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    Progress in design and development of battery thermal management system for electric vehicles
    (Springer, 2025-08) Verma, Saket
    Reversible electrochemical batteries having reasonable cyclic charging and discharging capabilities are commonly employed in portable applications. The battery technology has improved on various aspects such as high specific energy density, high nominal voltage (up to 3.7 V), long cycle life and low self-discharge, and reached to a level, where it can be incorporated in large-scale applications, e.g. Electric Vehicles (EVs). Lithium-ion (Li-ion) batteries are commonly used in light and heavy-duty vehicles nowadays due to its superior performance, long life, and high energy density. The battery is the most critical component in an EV, and its effectiveness decides the success of the vehicle. In terms of economics, the battery pack represents a significant portion of the overall cost of an EV. Therefore, not only optimum design but also operation and maintenance of the battery pack is considered crucial. In this regard, both high and low temperatures have a significant impact on the performance of the Li-ion battery. Temperature non-uniformity also leads to capacity differences among individual cells, ultimately affecting the overall performance of the battery pack. To enhance electrochemical performance, prolong battery life, and maintain optimal power performance, it is crucial to develop a Battery Thermal Management System (BTMS) that can effectively and reasonably regulate its temperature. Most of the electrical automobile industries have adopted active cooling systems, including both air and liquid cooling. Air cooling systems are simple and low maintenance. However, due to the low heat transfer coefficient, the core part of the battery generally reaches high temperatures, leading to high thermal non-uniformity. Liquid cooling, on the other hand, has a higher heat transfer coefficient, which helps in creating a more effective cooling system. However, liquid cooling requires an external cooling system and a very effective leak-proofing, making it generally costlier. The energy provided to the active system is extracted from the battery pack, compromising the vehicle’s range. Passive cooling systems come into play as they are capable of eliminating or reducing these issues. However, passive techniques alone cannot provide effective cooling during high discharge and charging conditions. It is recommended to use a combination of passive and active techniques in BTMS to achieve the desired maximum temperature and thermal uniformity.
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    Towards sustainable transportation: factors influencing electric vehicle charging stations development
    (Elsevier, 2025-05) Digalwar, Abhijeet K.; Routroy, Srikanta
    The Indian transportation sector, reliant on fossil fuels, is predominantly accountable for the emergence of critical challenges such as greenhouse gas emissions, reliance on foreign energy sources, economic strain, and persistent health repercussions. In order to mitigate these urgent challenges, electric vehicles (EVs) are conceptualised as a viable, sustainable and ecologically sound technological solution, capable of successfully transitioning towards a sustainable low-carbon emission transportation framework and preserving finite natural resources. EVs encounter significant challenges in achieving rapid assimilation into the commercial landscape, and one of the most frequently referenced impediments to the accelerated adoption of EVs is the insufficiency of charging infrastructure along with the resultant range anxiety. Nevertheless, expanding the charging infrastructure network is financially burdensome and necessitates careful and strategic planning. Despite identifying essential factors, the inquiry “In what manner do these factors engage and interact?” has predominantly remained unaddressed in empirical investigations. Examining the interactions between these variables will empower producers and regulatory authorities to participate in systematic planning and devise suitable measures to govern these variables. The prime objective of this research is to execute an exhaustive assessment and furnish insights into the multifaceted factors/criteria influencing the establishment and development of EV charging infrastructure within a developing nation such as India. Factors are extracted from previous studies through literature reviews and expert interviews. The study also validates the identified factors empirically. Subsequently, a mixed-method approach is utilised to implement a combination of Interpretive Structural Modeling (ISM) and Decision-Making Trial and Evaluation Laboratory (DEMATEL). This methodology enables a methodical exploration of the hierarchical structures and interconnections among the variables, thereby enhancing the comprehension of their influence on the implementation and efficacy of charging infrastructure. The study identifies technological, economic, political, geographical, environmental, geopolitical, and socio-technical factors as key drivers influencing EV charging infrastructure development, highlighting the interdependencies between critical variables and providing a structured framework to enhance accessibility, scalability, and sustainability in alignment with global Sustainable Development Goals (SDGs) 7 and 13.
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    Assessment of optimal fuel and drive mix for automobile sector decarbonization in India: a scenario analysis of 2035
    (Springer, 2025-08) Digalwar, Abhijeet K.
    The rapid growth of predominantly fossil fuels powered automobiles in India results in harmful greenhouse gas emissions (GHG), environmental challenges like air pollution and health hazards. Hence, India is adopting alternate low-emission fuels like compressed natural gas (CNG), biofuels, promoting zero-emission technologies like fully electric vehicles (FEVs), pursuing options like hybrid vehicles (HEVs), and hydrogen-powered vehicles (HPVs). These solutions must encompass reliability, cost-effectiveness, circularity, and mainly optimality. This study addresses above challenges, aligns with India’s upcoming nationally determined contribution (NCD 3.0) and decarbonization policy till 2035 and derives an optimal alternate fuels/drive mix, It adopts a time-series forecasting and machine learning (ML) for vehicle inventory projections, constructs a scientific model, includes six relevant cost and benefit factors, evaluates eleven scenarios using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, derives an optimal mix and verifies its robustness through sensitivity analysis. The optimal mix for 2035 indicates a reduction in the share of fossil fuels (50%) with healthy improvement in the adoption of FEVs (40%), BFVs (8.4%), CNGVs (0.6%), HEVs (0.5%), and HFVs (0.5%). This shift toward cleaner solutions will enable reduction of around Rs 3.6 trillion in fuel imports and 54% of GHG emissions compared to current levels, enabling mitigating environmental challenges. Unlike energy sector, India lags in studies of optimal fuel / drive mix for automobile sustainability. This study addresses above gap, providing critical insights to policymakers, industry, and academia for fine tuning automotive decarbonization policies, toward achieving net zero by 2070.
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    Development of a fuzzy-pi tuned bidirectional charger for electric three-wheeler applications
    (IEEE, 2025-05) Bansal, Hari Om; Singh, Dheerendra
    The growing worldwide market for electric vehicles (EVs) has put pressure on automotive system developers to improve charging efficiency and enhance the charging infrastructure. Bidirectional chargers support the grid by flowing the power in the two directions, i.e. functioning in both V2G and G2V modes. In this paper, a bidirectional converter interfaces a fixed DC bus that supports EV battery charging and discharging operation, is presented and simulated in a MATLAB environment. A Fuzzy Logic tuned Proportional Integral (FLPI) is designed using MATLAB Simulink to enhance the charger's performance. This paper also presents a performance comparative analysis of the FLPI and conventionally used PI Controller, highlighting the FLPI controller's advantages. FLPI is better than the conventional PI because of low errors, faster response time, better transient performance and improved robustness. The charger is developed and simulated for a 600V DC supply with a peak output power of 10kW. The simulation results demonstrate the charging and discharging of a 72V 150 Ah Lithium-ion (Li-ion) battery for electric-3-wheeler applications.
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    Hardware-in-loop implementation of an adaptive MPPT controlled PV-assisted EV charging system with vehicle-to-grid integration
    (Springer Nature, 2025-08) Bansal, Hari Om
    The penetration of electric vehicles (EVs) into society needs extensive charging infrastructure. The existing charging system solely depends on the grid supply, which is essentially fossil fuel-dependent and leads to carbon emissions and environmental pollution. This can be minimized by incorporating renewable energy into the charging grid. This article presents a charging scheme combining photovoltaic (PV) and grid, offering a clean and dependable charging plan to sustain green transport. The proposed work presents the modelling and controlling a 10 kW EV charging/discharging framework integrating PV and grid. This work has multi-fold objectives: i) the development of an intelligent hybrid maximum power point tracking (MPPT) strategy, ii) the design of a fuzzy logic controlled bidirectional charger, iii) the setup of a PV-grid integrated charging system, and iv) the implementation of vehicle-to-grid (V2G) operation. The proposed charging system utilizes PV power and seamlessly switches to grid power whenever required. Since the performance of the PV source is affected by varying temperatures and irradiance, MPPT methods are needed to extract maximum power from the PV source. This paper developed and compared perturb and observe (P&O), Particle swarm optimization (PSO), and hybrid PSO + Adaptive neuro-fuzzy inference system (ANFIS) based algorithm for MPPT. The findings indicate that the PSO + ANFIS-driven method offers the highest tracking efficiency of 99.5%. This algorithm is also tested under dynamic partial shading conditions (PSC) to ensure robustness, and it led to achieving fast convergence and high efficiency despite multiple power peaks. In addition, the designed bidirectional charging system maximizes solar energy collection, minimizes the charging cost, and improves grid stability through demand balancing. The overall system is validated in a hardware-in-loop real-time environment through FPGA-based OPAL-RT.
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    Electrocatalyst for the oxygen reduction reaction (ORR): towards an active and stable electrocatalyst for low-temperature PEM fuel cell
    (Springer, 2024-08) Pandey, Jay
    Green hydrogen–fueled low-temperature proton exchange membrane (PEM) fuel cells have emerged as one of the most attractive technologies for electric-vehicle (EV) applications due to their high efficiency, zero emissions, and potential for renewable energy integration. The performance of the PEM fuel cells is significantly affected by the electrochemical activity of the oxygen reduction reaction (ORR) catalyst. This review comprehensively examines the role of ORR electrocatalysts in PEM fuel cell efficiency for portable, transport, and stationary applications. In this direction, we discuss the fundamentals of PEM fuel cell operation, the critical role of electrocatalysts, and advanced characterization techniques. A detailed overview of ORR electrocatalyst types, including platinum-based, non-noble metal-based, and carbon-supported as well as noncarbon supported, is presented, emphasizing recent advancements in design and synthesis. The review concludes with discussing current challenges and future directions for ORR electrocatalyst development. Understanding the characteristics and recent developments of ORR catalysts is essential for researchers and engineers to optimize the performance and durability of PEM fuel cells, thereby promoting the wider adoption of clean and efficient energy technologies. By providing insights into electrocatalyst characteristics and emerging trends, this work aims to accelerate the adoption of clean and efficient PEM fuel cell technology.
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    Optimal scheduling of mobile and stationary electric vehicle charging stations in a distribution system with stochastic loading
    (Elsevier, 2025-07) Mishra, Puneet; Mathur, Hitesh Datt
    Due to surge in the use of electric vehicles (EVs), electric vehicle charging station (EVCS) load modelling emerges to be vital in designing or revamping existing EV charging facilities. The present work addresses this optimal scheduling problem by proposing a novel probabilistic model to predict the optimum demand at a charging station for fixed time duration and thereafter for variable durations using dynamic fault tree analysis considering the charging urgency of the vehicles. To cater to the increased load demand due to enhanced EV penetration and to mitigate its associated technical challenges, incorporation of Mobile Charging Station (MCS) is proposed in the present work. However, placement of MCS poses a significant challenge of their optimal siting and scheduling. This has been achieved by identifying priority areas for their positioning from a proposed Mobile Charging Station Allocation Indicator (MCSAI) computed based on escalated requirement at an EVCS. Extensive investigations have been conducted for placement of combination of fixed and mobile EVCS in a standard IEEE 33 and 85 bus distribution system and it is shown that the resultant hybrid system leads to a significant improvement of more than 5 %, 15 % and 25, 30 % respectively as measured by indices such as line loss reduction index voltage profile improvement index.
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    Performance assessment of a distribution system with electric vehicle charging station and forecasted loads
    (Springer, 2025-05) Mishra, Puneet; Mathur, Hitesh Datt
    A trend towards green transportation causes huge escalation in the use of electric vehicles. Therefore, proper evaluation of the burden on a charging changing station is immensely essential. This work propounds a novel technique based on probabilistic estimation of the total demand at an Electric Vehicle Charging Station (EVCS) for certain fixed hourly durations of time and then on the basis of vehicle categorisation dependent on the exigency of the vehicles. Based on the probabilistic estimation of EVCS loads, an optimum mix of charging stations is positioned strategically in an IEEE 33 bus distribution system designed on a methodology based on apparent power loss. The system with EVCS positioned at the optimal points is analysed with the help of two assessment indicators, namely line loss reduction index and voltage profile improvement index. The performance of the aforesaid system is strengthened by the addition of distributed generators at the aptly sited locations.