Energy Conversion and Management最新文献

{"title":"Research on virtual calibration technology for multi objective operating parameters of thermal management system based on thermodynamic indicators","authors":"Haoyuan Chen ,&nbsp;Kunfeng Liang ,&nbsp;Chunyan Gao ,&nbsp;Yunpeng Zhang ,&nbsp;Xun Zhou ,&nbsp;Bin Chen ,&nbsp;Chenguang Zhang ,&nbsp;Haolei Duan ,&nbsp;Shuopeng Li","doi":"10.1016/j.enconman.2025.119712","DOIUrl":"10.1016/j.enconman.2025.119712","url":null,"abstract":"<div><div>With the rapid development of battery electric vehicle, technical problems still exist, and an efficient and reliable thermal management system is a core challenge to improve vehicle performance.This study proposes a multi-mode directly-cooling thermal management system to meet temperature control requirements while optimizing energy efficiency, cost, and environmental impact. An experimental and simulation platform for the system was established as the data source, and a thermodynamic analysis architecture including three indicators was developed to evaluate the impact of different operating parameters on system performance using experimental data. The results show that a 5 °C increase in the system evaporation temperature reduced total energy loss by approximately 12.6 % and environmental impact by 4.65 %, while increasing costs by about 12 % in both modes, system has a set of optimal operating parameters under different operating modes. Under the guidance of thermodynamic analysis, three thermodynamic indicators and key operating parameters were optimized as objective functions and decision variables. The Non-dominated sorting genetic algorithm was applied to develop a multi-objective virtual calibration technology for system parameters, leading to an 18.2 % increase in exergy efficiency across both modes, along with reductions of 11.1 % in total cost rate and 30.9 % in environmental impact rate. Based on the AMESim platform, virtual calibration of optimized parameters demonstrates that the proposed scheme ensures temperature control performance while significantly improves energy efficiency, and reduces economic and environmental impacts, showing strong application potential.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119712"},"PeriodicalIF":9.9,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143619982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aerodynamics prediction of vertical-axis wind turbines based on meta learning under regional interactions","authors":"Rui Zhang ,&nbsp;Lingyu Zhan ,&nbsp;Redili Yushan ,&nbsp;Yaoran Chen ,&nbsp;Limin Kuang ,&nbsp;Yu Tu ,&nbsp;Zhaolong Han ,&nbsp;Dai Zhou","doi":"10.1016/j.enconman.2025.119727","DOIUrl":"10.1016/j.enconman.2025.119727","url":null,"abstract":"<div><div>Due to the difficulty in balancing efficiency and accuracy using traditional methods, an increasing number of deep learning models are being used to study the aerodynamic parameters of vertical-axis wind turbines. Nevertheless, interactions between the upwind and downwind regions of vertical-axis wind turbines were often ignored in this process, resulting in inaccurate outcomes. In a meta learning framework, this study proposes a novel deep learning model, called Meta-Double Long Short-Term Memory, to accurately predict aerodynamics of vertical-axis wind turbines. In this model, Double Long Short-Term Memory module utilizes the upwind region and downwind region models to characterize the interactions among regions, while model-agnostic meta-learning is used to capture knowledge across different datasets in a two-stage strategy. Experimental results indicate that this model outperforms other baselines with the lowest errors of 2.21 % and 1.85 % for the peak torque coefficient and the corresponding azimuthal angle, respectively. Global sensitivity analysis reveals that turbine rotational speed (<em>ω</em>) has the greatest impact on prediction results, while upwind aerodynamics and geometrical parameters also significantly affect downwind predictions. Additionally, the proposed model can effectively optimize turbine parameters and provides detailed time series of aerodynamic parameters for in-depth analysis. By using a meta-learning approach and considering regional interactions, the proposed model improves the accuracy of aerodynamic predictions for vertical-axis wind turbines, and its training methodology can be applied to other renewable energy systems.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":""},"PeriodicalIF":9.9,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Techno-economic and environmental impacts of hybridization and low-carbon fuels on heavy-duty trucks","authors":"Kangjie Liu ,&nbsp;Zhiyu Han ,&nbsp;Junbo Zhang ,&nbsp;Ziwei Tang ,&nbsp;Haifeng Tang","doi":"10.1016/j.enconman.2025.119634","DOIUrl":"10.1016/j.enconman.2025.119634","url":null,"abstract":"<div><div>Heavy-duty trucks account for a significant share of petroleum consumption and CO₂ emissions in the automotive sector. However, their transition to low-carbon renewable energy has lagged behind that of passenger vehicles. This study systematically evaluates the performance, energy consumption, total cost of ownership (TCO), and well-to-wheel (WTW) CO₂ emissions of various low-carbon fuel powertrains and fuel-electric hybrid systems for heavy-duty long-haul trucks. The fuels considered include liquefied natural gas (LNG), methanol, hydrogen, and electricity, while the hybrid systems evaluated are series, parallel, and series–parallel configurations. Design parameters of these diesel-electric hybrid systems were first optimized to achieve improved performance and cost-efficiency. The series–parallel design emerged as the most effective configuration and was subsequently applied to other fuel hybrid systems. The analysis revealed that hybrid trucks consistently outperformed conventional engine trucks in energy consumption, TCO, and CO₂ emissions across all fuel types. Diesel-, LNG- and methanol-electric hybrid trucks were more cost-effective than battery-electric trucks, underscoring hybridization as a pivotal technology for energy savings and emissions reduction in logistics. Hydrogen engine and hydrogen hybrid trucks exhibited higher TCOs compared to diesel-based systems, while LNG and methanol hybrid trucks offered the lowest TCOs, highlighting the economic barriers to widespread hydrogen adoption. The WTW CO₂ emissions were highly dependent on the production pathways of methanol and hydrogen. For instance, trucks fueled by coal gasification-derived hydrogen emitted 2.64 times the CO₂ of diesel trucks, whereas hydrogen produced from renewable electricity reduced CO₂ to just 29.3% of diesel levels. Similarly, coal-derived methanol increased CO₂ emissions by 3.95 times compared to diesel, while methanol synthesized from industrial CO₂ exhausts and hydrogen from coke oven gases achieved a 22.8% reduction. These findings highlight that transitioning heavy-duty trucks to methanol and hydrogen fuels requires a parallel shift toward sustainable, low-carbon fuel production methods to maximize environmental benefits.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119634"},"PeriodicalIF":9.9,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143610882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficiency enhancement of liquid air energy storage systems through ultra-high-temperature heat pump integration","authors":"Jiamin Du ,&nbsp;Xindong Wang ,&nbsp;Jiyun Liu ,&nbsp;Junxian Li ,&nbsp;Zhikang Wang ,&nbsp;Xiaoyu Fan ,&nbsp;Yihong Li ,&nbsp;Zhaozhao Gao ,&nbsp;Wei Ji ,&nbsp;Liubiao Chen ,&nbsp;Junjie Wang","doi":"10.1016/j.enconman.2025.119714","DOIUrl":"10.1016/j.enconman.2025.119714","url":null,"abstract":"<div><div>Liquid air energy storage is emerging as a promising technology for large-scale energy storage. It offers high energy density and geographical flexibility, making it an effective solution for grid peak shaving. However, the round-trip efficiency of standalone systems typically ranges from 50 % to 60 %, with insufficient utilization of compression heat being a key factor contributing to low efficiency. Enhancing the use of compression heat and increasing the reheat temperature during expansion are effective strategies for improving the performance of the system. This study proposes an innovative system that integrates an ultra-high-temperature heat pump unit with an organic Rankine cycle to address these challenges. The system leverages the ultra-high-temperature heat pump to upgrade compression heat, thereby raising the reheat temperature during the energy release phase and resolving the low reheat temperature issue common in traditional designs. Additionally, the organic Rankine cycle recovers and harnesses the waste heat from the compression process, generating additional power and improving the round-trip efficiency. A thermodynamic model was developed to design and optimize the system, achieving a round-trip efficiency of 63.14 %. Economic analysis further reveals that the dynamic payback period of the system is 6.82 years, with a net present value of 12.85 million USD over its operational lifespan, 2.13 times higher than that of standalone liquid air energy storage systems. These results demonstrate that the integrated system improves profitability and market competitiveness. By efficiently utilizing compression heat, the proposed system ensures safety, flexibility, and high efficiency, offering valuable insights for the development of large-scale standalone liquid air energy storage systems.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119714"},"PeriodicalIF":9.9,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143610886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advances and future perspectives in thermoelectric cooling technology","authors":"Lei Wang ,&nbsp;Tianshu Chu ,&nbsp;Shuaishuai Yuan ,&nbsp;Peng Zou ,&nbsp;Wenchao Zhai ,&nbsp;Xiaobing Zheng ,&nbsp;Maopeng Xia","doi":"10.1016/j.enconman.2025.119621","DOIUrl":"10.1016/j.enconman.2025.119621","url":null,"abstract":"<div><div>Thermoelectric cooling technology has become a research hotspot due to its alignment with the growing demand for environmentally friendly solutions. Compared to traditional cooling methods, thermoelectric coolers (TECs) offer advantages such as compact size, lightweight, simple structure, and lack of vibration. These benefits allow for easy integration with various power devices and enable precise temperature control. However, TECs face challenges including limited temperature control range and low thermoelectric conversion efficiency. This review explores the latest advancements in TECs across material design, structural design, heat dissipation, and application areas to identify potential solutions. The exploration of room-temperature thermoelectric materials with extremely low lattice thermal conductivity, high Seebeck coefficients, and high electrical conductivity is crucial for enhancing TEC performance. Investigating novel TEC structures and reducing thermal resistance between the TEC’s hot side and the heat sink will improve cooling efficiency. Additionally, optimizing system integration designs for TECs can support low-cost, large-scale commercialization. This review outlines the challenges TECs will face in the future and provides possible solutions. Addressing these issues will significantly boost TECs’ competitiveness within the broader cooling technology landscape.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119621"},"PeriodicalIF":9.9,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143620087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wake dynamics of a wind turbine under real-time varying inflow turbulence: A coherence mode perspective","authors":"Hao Yue ,&nbsp;Hongfu Zhang ,&nbsp;Qingchi Zhu ,&nbsp;Yifeng Ai ,&nbsp;Hui Tang ,&nbsp;Lei Zhou","doi":"10.1016/j.enconman.2025.119729","DOIUrl":"10.1016/j.enconman.2025.119729","url":null,"abstract":"<div><div>Turbulence plays a pivotal role in the aerodynamic performance and wake dynamics of wind turbines; however, current numerical simulation studies often overlook its effects or simplify them through modeling, leading to significant deviations and discrepancies from real-world conditions. To address this gap, this study proposes an active narrowband synthesis random flow generation method for real-time inflow turbulence generation at the inlet of the National Renewable Energy Laboratory’s offshore 5 MW wind turbine using large eddy simulation. This study examined the impact of turbulence on vortex dynamics in the wind turbine wake, employing higher-order dynamic mode decomposition to analyze coherent modes. The results indicate that turbulence and tip speed ratio significantly influence the aerodynamic behavior of the wind turbine. The turbulence alters the wake’s velocity distribution, producing a more skewed, oblique W-shaped configuration, while enhancing fluctuating wind energy at specific frequencies. Additionally, the effects of turbulence are predominantly concentrated in the modes with <em>f_n</em> = 1 and <em>f_n</em> = 2, with turbulence disrupting the stability of tip vortices in the far wake while preserving the stability of near-wake vortices at high tip speed ratios. As rotor speed decreases, turbulent effects increasingly dominate the wake vortex characteristics. This study concludes that turbulence, particularly when combined with a reduction in tip speed ratio, accelerates the destabilization of tip vortices, leading to more complex vortex structures in the near wake.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119729"},"PeriodicalIF":9.9,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143610885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advances in protective coatings for porous transport layers in proton exchange membrane water electrolyzers: Performance and durability insights","authors":"Leila Moradizadeh ,&nbsp;Pramoth Varsan Madhavan ,&nbsp;Adnan Ozden ,&nbsp;Xianguo Li ,&nbsp;Samaneh Shahgaldi","doi":"10.1016/j.enconman.2025.119713","DOIUrl":"10.1016/j.enconman.2025.119713","url":null,"abstract":"<div><div>Proton exchange membrane water electrolyzers offer a promising pathway for sustainable hydrogen production. However, the high cost and limited durability of key components, particularly porous transport layers, hinder their widespread adoption. The porous transport layer enables water and electron transport and oxygen removal. Titanium typically enables the required durability, yet the oxidative conditions lower its electrical conductivity. Protective coatings on porous transport layers play a pivotal role in enhancing electrochemical performance and durability by mitigating interfacial contact resistance and maintaining structural integrity under harsh oxidative conditions. This Review highlights the critical impact of porous transport layer coatings on the electrochemical performance and durability by comparing various porous transport layer coatings, including precious metals, non-precious metals, and their combinations. It clarifies the desirable coating material specifications, along with the appropriate morphological, structural, and physical characteristics of the resulting porous transport layers. It also provides a detailed comparative analysis of polarization characteristics, electrochemical impedance responses, potentiostatic and potentiodynamic polarizations, and interfacial contact resistances for various porous transport layer coatings. This Review overviews coating materials and highlights the promising candidates to be considered in the design of next-generation porous transport layers for proton exchange membrane water electrolyzers. The Review assesses the porous transport layer materials from various aspects, including performance, durability, and scalability – all centered around practicality. The Review concludes with the recent progress, remaining challenges, and future research directions.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119713"},"PeriodicalIF":9.9,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143610884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fuel cell system humidity regulation and shutdown purge strategy using observer-based model predictive control to improve Time-to-Target and compressor energy performance","authors":"Haowen Hu ,&nbsp;Fengxiang Chen ,&nbsp;Bo Zhang ,&nbsp;Xuncheng Chi ,&nbsp;Fenglai Pei ,&nbsp;Su Zhou","doi":"10.1016/j.enconman.2025.119666","DOIUrl":"10.1016/j.enconman.2025.119666","url":null,"abstract":"<div><div>The accumulation of water in fuel cell operation significantly influences its longevity and efficiency. This study focuses on humidity control and shutdown purge strategies in fuel cell systems, utilizing model predictive control (MPC) based on a fuel cell humidity sliding mode observer (SMO). The primary objective is to improve the time taken to reach set objectives and the energy efficiency of the air compressor in the fuel cell system. This will be achieved by adjusting the cathode air flow rate to manage humidity levels effectively, particularly during high-load operations and system shutdown. Experimental analysis conducted on an 80 kW Proton Exchange Membrane Fuel Cell system reveals that the observer’s estimations demonstrate remarkable accuracy, particularly for currents exceeding 100 A, showing minimal deviation from experimental results, with an overall relative error below 5 %. Simulations conducted under specifically designed conditions and the New European Driving Cycle demonstrate that the SMO-based MPC method enhances the efficiency of fuel cell humidity control and shutdown purging processes by reducing time and energy consumption by more than 40 % and 30 %, respectively, in comparison to fixed flow rate and interval flow rate methods. Moreover, the Hardware-in-Loop experimental results indicate that the developed SMO-based MPC method exhibits promising real-time operational capabilities, with the maximum relative error not exceeding 0.05 between simulation and experimental outcomes.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119666"},"PeriodicalIF":9.9,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"4E performance evaluation of renewable microgrids: Comparing hydrogen and battery storage for nearly net zero energy buildings","authors":"Zahra Piryaei ,&nbsp;Aslan Gholami ,&nbsp;Majid Zandi","doi":"10.1016/j.enconman.2025.119711","DOIUrl":"10.1016/j.enconman.2025.119711","url":null,"abstract":"<div><div>Renewable microgrids and decentralized power generation have recently emerged as sustainable solutions for powering standalone nearly-net-zero buildings. This study proposed two photovoltaic-based microgrids: one with hydrogen energy storage and the other with battery energy storage, to supply the real-time energy needs for electrical appliances, heating, cooling, and hot water at a research office. Both systems are designed to achieve a levelized cost of energy of 0.78 EUR/kWh. Simulated using TRNSYS 18 software with a dynamic power load following model, the systems have been evaluated based on Energetic, Exergetic, Economic, and Environmental (4E) criteria over the first year of operation. The hydrogen-based system comprises a 13.1-kWp photovoltaic array, a 7-kW alkaline electrolyzer, and a 3.5-kW fuel cell. In contrast, the battery-based system includes a 150-kWh lead-acid battery. The hydrogen-based system fully meets the electrical demand with a loss of load probability of 0% and provides hot water through waste heat recovery from the fuel cell. The battery-based system, however, results in a loss of load probability of 4.34%. Both systems exhibit similar overall energy efficiencies but slightly different exergy efficiencies. The first system achieves 12.37% and 14.33%, respectively, while the second system achieves 12.28% and 20.8%. Despite the battery-based system having a higher energy dump, it boasts a greater round-trip efficiency of 90.23% compared to 46.86% for the hydrogen-based one. Both configurations avoid annual greenhouse gas emissions of about 8.5 tCO₂ eq. Therefore, they can be considered sustainable alternatives for cleaner energy production, significantly contributing to carbon footprint minimization.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119711"},"PeriodicalIF":9.9,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143610883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative analysis of thermal management systems in electric vehicles at extreme weather conditions: Case study on Nissan Leaf 2019 Plus, Chevrolet Bolt 2020 and Tesla Model 3 2020","authors":"Rabih Al Haddad ,&nbsp;Charbel Mansour ,&nbsp;Namdoo Kim ,&nbsp;Jigu Seo ,&nbsp;Kevin Stutenberg ,&nbsp;Maroun Nemer","doi":"10.1016/j.enconman.2025.119706","DOIUrl":"10.1016/j.enconman.2025.119706","url":null,"abstract":"<div><div>With the surge in electric vehicle (EV) adoption and the need for extended driving ranges, optimizing energy efficiency, particularly through thermal management, is critical, especially in extreme weather. Managing the substantial energy needed for cabin climate control and battery temperature regulation can increase energy demands by over 50 %, severely limiting range. This study conducts a comparative analysis of thermal management systems (TMS) in three popular EV vehicles, 2020 Chevrolet Bolt, 2019 Nissan Leaf Plus, and 2020 Tesla Model 3, evaluating their distinct TMS configurations and performance under varied weather conditions. Using both numerical simulations and experimental data collected on a controlled test bench at Argonne National Laboratory, we assess how TMS architecture and operational modes influence energy consumption and range. A comprehensive TMS model was developed, integrating cabin and battery thermal sub-models in the Autonomie software platform, to simulate temperature fluctuations and range impacts. Cabin climate was modeled using a mono-zonal approach, while battery cell temperature distribution was estimated through a 2D nodal structure. Each vehicle’s distinct TMS setup was evaluated: the Chevrolet Bolt and Tesla Model 3 use a dual evaporator vapor compression cycle with a PTC heater for the cabin and a coolant loop for battery thermal management; the Nissan Leaf Plus employs a heat pump with a PTC heater for the cabin and air-cooling for the battery. Tests conducted at ambient temperatures of 35 °C, 22 °C, −7°C, and −18 °C reveal significant differences in energy use and range reduction across both configurations and conditions. At 35 °C, the Tesla Model 3, Chevrolet Bolt, and Nissan Leaf Plus have a range reduction of 8 %, 9 %, and 13 %, respectively, due to air conditioning. In winter, heating technology is paramount; at −7°C, the Nissan Leaf’s heat pump configuration achieves a lower range reduction (19.3 %) compared to the Tesla and Chevrolet Bolt PTC heaters, which reduce range by 28.3 % and 31 %, respectively. This study provides valuable insights for automotive engineers, EV technology researchers, and thermal management system designers aiming to enhance electric vehicle performance by understanding how different weather conditions and TMS architectures impact energy consumption and driving range.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119706"},"PeriodicalIF":9.9,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143592920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}