IET Electrical Systems in Transportation最新文献

{"title":"Access to a Wireless Charge Station, Impact on Eco-Cooperative Driving at Signalized Intersections","authors":"Ali Parsi,&nbsp;Teymoor Ghanbari,&nbsp;Ebrahim Farjah","doi":"10.1049/els2/2506022","DOIUrl":"https://doi.org/10.1049/els2/2506022","url":null,"abstract":"<p>Electric vehicles (EVs) have been considered a sustainable solution for greenhouse gas emissions mitigation. Range anxiety and limited battery capacity hinder the mass adoption of EVs. Addressing the issue of decreasing energy consumption is critical for the efficiency of EV operation. The fast-paced advancement in connected and automated technologies enables EVs to optimize speed trajectory and minimize energy consumption with the help of eco-driving. In this study, we propose a novel eco-cooperative driving before and beyond a signalized intersection, considering a wireless charge station beyond the intersection. First, the eco-cooperative driving strategy is developed for a single vehicle in free-flow traffic. Then, the proposed eco-cooperative driving strategy is developed for mild traffic density, considering queue length. The optimum eco-cooperative driving is determined using an approach based on the particle swarm optimization (PSO) method. According to the results, the proposed eco-cooperative driving strategy could reduce travel costs up to 19.50%. Moreover, the safety of the EV is ensured by avoiding stopping in the middle of the road due to complete battery discharge.</p>","PeriodicalId":48518,"journal":{"name":"IET Electrical Systems in Transportation","volume":"2026 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/els2/2506022","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149146773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Accelerated-Life Assessment and Condition-Based Replacement-Interval Extension of Voltage Sensor Modules in Urban Rail Power Systems: A Shenzhen Metro Case Study","authors":"Wenkang Zhang,&nbsp;Zhe Chen,&nbsp;Wenba Li,&nbsp;Liang Wang,&nbsp;Xiaohai Li,&nbsp;Zhanpeng Jin","doi":"10.1049/els2/4345782","DOIUrl":"https://doi.org/10.1049/els2/4345782","url":null,"abstract":"<p>With the aging of urban rail fleets and increasing pressure to reduce life cycle maintenance costs, extending the service life of key electrical components has become an important engineering issue. This study assesses the service life of Siemens voltage sensor modules used in the Shenzhen Metro power system and evaluates a conditional extension of their replacement interval. Accelerated life tests were conducted under high-temperature and combined high-temperature/high-humidity conditions using an extended Arrhenius model. The results indicate that a mean field-equivalent time to nonconformance approaching 15 years may be obtained at a damage-equivalent relative humidity of ~53.6% at a reference temperature of 42°C, under the adopted acceleration model and duty-cycle assumptions. Comparative tests on long-serving sensors and historical field failure records further support their continued serviceability beyond the current 10-year replacement interval. Accordingly, a condition-based 15-year replacement strategy is proposed, in which environmental humidity management and periodic field verification are required to ensure continued serviceability. A life cycle cost model with scenario sensitivity analysis further demonstrates the economic advantage of the adjusted strategy under typical increases in failure rate and single-failure cost. These results suggest that a condition-based 15-year replacement cycle is technically and economically feasible when appropriate environmental management and field validation are ensured.</p>","PeriodicalId":48518,"journal":{"name":"IET Electrical Systems in Transportation","volume":"2026 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/els2/4345782","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148994067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Novel Scaling Methods for Predicting Electric Motor Energy Consumption From Reduced-Scale Tests","authors":"Kaarlo Mäkelä,&nbsp;Markus Rumjantsev,&nbsp;Jenni Pippuri-Mäkeläinen,&nbsp;Jesse Pirhonen,&nbsp;Risto Ojala","doi":"10.1049/els2/3451390","DOIUrl":"https://doi.org/10.1049/els2/3451390","url":null,"abstract":"<p>The rush to develop electric powertrains has led vehicle manufacturers to adopt early testing strategies such as hardware-in-the-loop (HIL) simulation. The electric motor may be operated under a simulated environment in a HIL arrangement; however, early-stage testing may also call for reduced-scale experimentation. This study examines the feasibility of predicting the energy consumption of a vehicle motor using measurements from a smaller surrogate motor. Two novel scaling methods are developed and compared against a baseline method used in previous research. One utilizes analytical relationships between electrical properties to scale copper and iron losses, while the other compares known efficiency maps of both motors. These methods scale our measurements up to predict the energy consumption of a motor from a real application. To evaluate the accuracy of our predictions, we compare against measured energy consumption from the application motor. Our analytical scaling method utilizing electrical motor parameters reduced prediction error by 18% from baseline, while empirical scaling with efficiency maps reduced it by 49%, improving prediction accuracy in both cases.</p>","PeriodicalId":48518,"journal":{"name":"IET Electrical Systems in Transportation","volume":"2026 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/els2/3451390","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148943202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Modeling and Control of Rail Potential With Partial Backflow Obstruction in DC Metro Systems","authors":"Qiaoyue Li,&nbsp;Xin Zheng,&nbsp;Tongtong Zhou,&nbsp;Guifu Du,&nbsp;Fengchuan Xu","doi":"10.1049/els2/9956380","DOIUrl":"https://doi.org/10.1049/els2/9956380","url":null,"abstract":"<p>Running rails are employed as the reflux conductor in DC metro systems, whose longitudinal resistance and joint resistance usually increase with the operating years of the system. Subsequently, the partial backflow obstruction occurs, which will greatly increase rail potential (RP) and endanger the security of the metro line operation. In this paper, a dynamic calculation model of DC metro systems with coupled multiple reflux paths is proposed to study the effect and control method of partial backflow obstruction. Firstly, the dynamic simulation model with coupled multiple reflux paths of DC metro is proposed, and the equivalent chain circuit and unified node admittance matrix are established with partial backflow obstruction. Secondly, the effect of backflow obstruction in DC metro systems is studied for the first time with multiple trains operating in Guangzhou Metro Line 2. Thirdly, the control method of partial backflow obstruction with parallel low-resistance reflux conductors is proposed, and the effectiveness of the control method is analyzed. Results show that partial backflow obstruction will seriously raise the dynamic RP in nearby sections, and the parallel low-resistance reflux conductors can effectively restrain the influence of backflow obstruction.</p>","PeriodicalId":48518,"journal":{"name":"IET Electrical Systems in Transportation","volume":"2026 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/els2/9956380","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148496797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Dynamic Matching of Photovoltaic Energy Supply and Demand on Highway Based on Transformer Method of Deep Learning","authors":"Changhao Li,&nbsp;Puda Dai,&nbsp;Yubian Wang,&nbsp;Jia He","doi":"10.1049/els2/5572580","DOIUrl":"https://doi.org/10.1049/els2/5572580","url":null,"abstract":"<p>In the era of rapid transportation electrification, the integration of power system automation and transportation system networking promotes the construction of comprehensive integration of the highway industry. Due to the huge project and the difficulty of construction, traditional highway construction cannot fully consider the supporting construction of electrification and networks and often lays monitoring and network facilities near the power facilities around the path. With the maturity of photovoltaic and other new energy technologies, and considering the increasing demand for modern highways, we put forward the design requirements and transformation standards of energy-supporting facilities. Based on the whole path, the power-supporting projects are realized to establish a new highway project with electrification, networking, and whole-process monitoring. This study addresses the issue of supply–demand mismatch in photovoltaic energy by proposing an integrated nonlinear regression framework based on the Transformer architecture to impute missing data. Considering the impact of energy storage conversion energy loss on the calculation effect of the model, and the input unit extracts the global degradation external characteristics, the long linear regression model is used to design the potential of recurrent neural network (RNN) shallow feature extraction. Multiple parallel RNN-transformer (RNN-T) are set to extract the external characteristics of power supply and demand balance without sharing the relevant parameters. The experimental process in the simulation platform built has verified that the model established in this study reduces the complexity and eases the accuracy error caused by data calculation. While in the matching ability and prediction accuracy, the test results are significantly better than the traditional method because its overall performance is improved by 25.2% and 29.7%, respectively, which supports that the improved model can learn the relationship between multilayer heterogeneous data simultaneously. Therefore, it improves the model’s deep learning ability in the photovoltaic power supply and demand relationship model. High-precision prediction effect is also achieved, which has great market value and practical significance for future road development.</p>","PeriodicalId":48518,"journal":{"name":"IET Electrical Systems in Transportation","volume":"2026 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/els2/5572580","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148282163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Recent Advances in Hybrid, Plug-In, Battery, and Fuel Cell EVs: Control Schemes, Modes, Converter Topologies, and Pros and Cons","authors":"Abhilash Sakhare,&nbsp;Suresh Mikkili,&nbsp;Praveen Kumar Bonthagorla","doi":"10.1049/els2/9670895","DOIUrl":"https://doi.org/10.1049/els2/9670895","url":null,"abstract":"<p>Direct current (DC)–DC converters are the backbone of electric vehicle (EV) power trains, enabling efficient and bidirectional energy flow between the battery, high-voltage (HV) DC link, and auxiliary rails under tight isolation, gain, ripple, and electromagnetic interference (EMI) constraints. This review catalogs 29 EV DC–DC converter families and classifies them by isolation requirement, gain window, bidirectionality, and ripple tolerance. On the implementation side, we survey modern control-digital voltage/current-mode (VMC/CMC), model-predictive/model-free, and artificial intelligence (AI)–assisted scheduling-together with protections (device level desaturation/soft turn-off through contactor policy) and thermal/EMI codesign (hot-loop minimization, spread spectrum, common-/differential-mode filtering). Normalized benchmarks at three representative operating points-auxiliary 12–48 V, mid-rail 48–800 V, and traction 350–1000 V show dual active bridge (DAB) and inductor–inductor–capacitor/capacitor–inductor–inductor–capacitor (LLC/CLLC) at 96%–98% for isolated HV links and on-board chargers (OBCs), interleaved buck–boost and multidevice interleaved bidirectional converters (MDIBCs) at 97%–98% for nonisolated bus ties, and multi-input power electronic converters/boost stages (PECs/boost) at 92%–96% with superior source decoupling. We provide a selection matrix mapping battery EV/hybrid EV/plug-in hybrid EV/fuel cell EV (BEV/HEV/PIHEV/FCEV) functions to topologies, a grid-to-vehicle ↔ vehicle-to-grid (G2V↔V2G) mode transition procedure, and 2020–2025 updates (silicon-carbide/gallium-nitride [SiC/GaN] devices, single-/triple-phase shift (SPS/TPS) and variable-frequency scheduling, and predictive/digital control). No single converter is universally optimal; choices balance isolation and gain against ripple limits, control complexity, EMI/thermal budgets, and cost.</p>","PeriodicalId":48518,"journal":{"name":"IET Electrical Systems in Transportation","volume":"2026 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2026-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/els2/9670895","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148237725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":48518,"journal":{"name":"IET Electrical Systems in Transportation","volume":"2026 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2026-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148096642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on DBSCAN-GMM-Based Probability Density Modeling for Traction Harmonics Analysis","authors":"Zijun Wei,&nbsp;Shiwu Yang,&nbsp;Yong Cui,&nbsp;Jingyuan Zhang,&nbsp;Chang Liu","doi":"10.1049/els2/3517372","DOIUrl":"10.1049/els2/3517372","url":null,"abstract":"<p>The accurate estimation of the probability distribution of traction current harmonics in EMUs is crucial for preventing electromagnetic interference (EMI), managing high-speed railway signaling systems, and analyzing traction system power quality. Although kernel density estimation (KDE) has been a longstanding flexible, nonparametric estimation method, it faces significant challenges, including high computational demands and difficulties in selecting appropriate bandwidths. This article introduces the Gaussian mixture model (GMM) as a novel approach for the probabilistic estimation of traction current harmonics, thereby providing a scientific foundation for harmonic analysis. To improve the precision and efficiency of harmonic interference assessments, we initialize the GMM parameters and the expectation-maximization (EM) algorithm with the density-based spatial clustering of applications with noise (DBSCAN). The effectiveness of our method is confirmed through the Kolmogorov–Smirnov (K–S) goodness-of-fit test, root mean square error (RMSE), and <i>R</i>² statistics, demonstrating that our approach provides greater stability and faster computation than existing methods.</p>","PeriodicalId":48518,"journal":{"name":"IET Electrical Systems in Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/els2/3517372","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145887575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":48518,"journal":{"name":"IET Electrical Systems in Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148095203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-Time User-Centric Routing Leveraging DG–DRM Integration in the Real-Time Distribution Network","authors":"Aishwarya Sadagopan,&nbsp;Nayanatara Chandrasekaran,&nbsp;Baskaran Jeevaratthinam","doi":"10.1049/els2/9959569","DOIUrl":"10.1049/els2/9959569","url":null,"abstract":"<p>The rapid adoption of electric vehicles (EVs) poses new challenges for both transportation networks and power distribution systems. To address these issues, effective EV routing strategies are essential to minimize grid stress and ensure efficient energy utilization. This research proposes an optimal EV routing by incorporating user-centric parameters and coordination of demand response management (DRM) with distributed generation (DG), facilitating effective synergy between user preferences and grid operational reliability. A loopless route is formulated considering distance and travel time (TT) to minimize the routing cost using Yen’s algorithm (YA). The optimized route, integrated with DG–DRM, ensures the minimization of power loss (PL) and the maximization of customer benefit (CB) using population-based incremental learning (PBIL) algorithm. To enable effective coordination between EV routing and DRM in the distribution network, the Monte Carlo sampling method is employed to validate stochastic traffic and load variations. IEEE-33 bus and the Indian utility power system (IUPS) network comprising 17 busses, are taken as test systems. The proposed methodology is compared with other soft computing techniques, and the findings demonstrate its superiority by achieving a 12.3% reduction in routing cost (RRC), a 16.74% reduction in PL, and a 22.31% increase in CB.</p>","PeriodicalId":48518,"journal":{"name":"IET Electrical Systems in Transportation","volume":"2025 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/els2/9959569","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145846060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}