Browse Topic: Vehicle charging

Items (1,166)
Plug-in Hybrid Electric vehicles (PHEVs) have the capability to effectively utilize electricity from the grid as an energy source for powering an appreciable portion of the total vehicle miles travelled (VMT), thereby reducing greenhouse gas (GHG) emissions, since the Carbon Intensity (CI) of electricity is often less than that of liquid fuels in many parts of the world. Several real-world usage factors can affect the fraction of VMT electrified, with the frequency of charging being one of the most influential factors. Studies in recent years have attempted to characterize the real-world performance of PHEVs based on long-term average fuel consumption and/or other data flags in the readout from vehicle On-Board Diagnostics (OBD), but such approaches are unable to infer accurate estimates for the occurrence of charging events. This paper adopts an approach that relies on analysis of highly granular (trip by trip) information obtained from vehicles equipped with a data communication
Hamza, KarimLaberteaux, Kenneth
Regenerative braking has a strong influence on the energy efficiency and drivability of battery-electric vehicles. This study establishes an empirical baseline analysis under controlled conditions of the regenerative braking behavior of the 2020 Tesla Model 3 to support the interpretation of on-road performance and serve as a reference for subsequent testing and analysis. The tests were performed on a four-wheel-drive chassis dynamometer at Argonne National Laboratory, combining Multi Cycle Testing (MCT) to simulate real world driving patterns (city, highway) with coast-down tests to isolate periods where the motor is operating in regen mode and compare the behavior across different parameters. Vehicle data was collected from the vehicle using taps in the Controller Area Network (CAN) bus as well as a high-resolution power analyzer. The vehicle displayed the highest efficiency during simulated city driving conditions (3.62 miles/kWh followed by highway (3.40 miles/kWh) and aggressive
Pierce, Benjamin BranchDi Russo, MiriamDas, DebashisZhan, LuStutenberg, Kevin
This paper presents research and digital twin modeling results to support work on a methodology to properly account for the energy consumed by the thermal system of a BEV, for use within both existing Petroleum-Equivalent Fuel Economy (PEFE) calculations, and the proposed addition of hot and cold weather range values to the consumer-facing Monroney label [1]. Properly accounting for thermal system impacts would incentivize minimizing energy consumption of these systems, since 1) BEV PEFE is a direct input to an OEMs overall CAFE performance, and 2) the values on the Monroney label has some impact on consumer vehicle choice. The impetus for this work was Final Rules issued by the EPA and NHTSA in early 2024 eliminating A/C Efficiency Credits for BEVs from the 2027 MY, thus eliminating regulatory incentives to minimize energy consumption of these systems. Higher energy consumption will produce a number of negative secondary effects, including higher real-world greenhouse gas emissions
Taylor, Dwayne
This paper explores the application of an Improved Enhanced-Boost Quasi-Z-Source Inverter in AC-connected extreme fast charging (XFC) stations for electric vehicles (EVs), aiming to reduce conversion stages and enhance system efficiency. AC-connected XFCs offer superior reliability compared to DC-connected systems due to better fault tolerance and reduced sensitivity to power fluctuations but traditionally suffer from increased complexity and reduced efficiency due to multiple conversion stages. The proposed inverter addresses this by combining DC-DC and DC-AC conversion into a single stage, simplifying the system, decreasing losses, and improving efficiency. Furthermore, this research investigates the use of Spiking Neural Networks (SNNs) for generating the precise pulse width modulation (PWM) signals required for the Quasi-Z-Source Inverter. SNNs offer potential advantages in terms of dynamic response and adaptability compared to traditional PWM techniques, allowing for optimized
Saliesh, DileepSanaboyina, PrudhviChhagar, RohnitsinghSatyanarayan, Swapna
This study presents a torque distribution control strategy for EVs with e4WD powertrain to overcome the trade-off between ensuring vehicle acceleration and deceleration responsiveness and mitigating backlash shock in the driving system. The deterioration of the drivability which occurs from the intrinsic hardware characteristics of the drivetrain is prevented by designing a response-priority drive mode in which neither front or rear motor torque is allowed to change its sign. Instead, in such drive mode, the front motor torque is only allowed to perform regenerative braking while the rear motor torque is only allowed to produce positive acceleration torque. In order to avoid sacrificing the maximum acceleration by applying such strategy, the mode transition function is implemented as well. In addition, in order to prevent backlash impact due to drivetrain compliance, variable offset torque based on drivetrain compliance model is evaluated in real time and applied to each motor command
Oh, JIWONLee, Ho Wook
Improving the energy efficiency of electrified vehicles remains a central objective in modern electric powertrains. Multi-level converters (MLCs) are widely recognised for lowering conversion losses relative to two-level inverters and improving total harmonic distortion (THD) in the sinusoidal supply to motors with a consequent reduction in motor losses. Despite this, sustained production-oriented validation at the integrated system level remains limited. This work introduces a multi-level converter architecture of the Battery Integrated Modular Multi-Level Converter (BIMMC) topology using Cascaded H-Bridge (CHB) architecture. It offers improvements in all key metrics of performance, cost, package size, mass and robustness compared to the current state-of-the-art two-level inverter system with distributed functions for charging available in the market today. The overall solution is highly functionally integrated. It supports four major functions required in electric vehicles without
Bao, RanKalaiselvan, PrashanthRener, KristofHallam, PhilipShi PhD, KaiYue, WilliamMa, HeGrimshaw, AndrewPatel, Simon
Electric vehicles (EVs) are central to sustainable transport, yet battery service life remains a limiting factor for cost and adoption. Distinct from traditional laboratory-based simulations that often fail to capture the complexity of field conditions, this study investigates how EV user behavior—including driving style and charging demands—influences capacity using large-scale, real-world operational data from daily EV usage. A data-driven framework is developed to quantify driving and charging behaviors through multidimensional feature extraction at the vehicle level and estimate battery State-of-Health (SOH) trajectories, enabling direct linkage between individual behavior patterns and degradation outcomes. Results reveal substantial heterogeneity in aging rates explicitly driven by diverse user behaviors: under identical urban conditions, vehicles with a radical driving style exhibit approximately 81% faster SOH decline per 20,000 km than those with a moderate style; regarding
Liu, TianyiJing, HaoZhu, JiankuanChen, YongjianOu, ShiqiQian, Xiaodong
Developing efficient fast-charging infrastructure along highway corridors is critical for reducing range anxiety and promoting long-distance electric travel. However, traditional static location approaches often fail to account for the stochastic interactions between continuous traffic flows and the stochastic variability of remaining driving ranges. To address these methodological gaps, this study develops a demand-driven optimization framework that integrates an improved Genetic Algorithm with the flow-capturing location-allocation model (GA-FCLM). Unlike static facility location approaches, the flow-capturing location-allocation component is specifically selected to maximize the interception of continuous traffic flows under strict range constraints, while the genetic algorithm efficiently navigates the high-dimensional discrete search space of simultaneous siting and sizing decisions. By synthesizing segment-level traffic flows with Monte Carlo simulations of state of charge (SOC
Guo, HaifengZhang, JingzhongLian, Jintao
Battery modules operate under diverse and complex conditions, such as driving cycles and fast charging. In these scenarios, effective thermal management is critical to ensuring safety and extending the battery's lifespan. Fast-charging scenarios present a particular challenge due to the complex current control strategies that strongly influence cell temperature distribution, making thermal uniformity a key concern. Existing studies focus more on drive cycles, but not sufficient for fast charging. This study presents a coupled electrochemical-thermal simulation framework based on the DCIR (Direct Current Internal Resistance) model to examine heat generation and temperature responses during fast charging. The model incorporates heat conduction pathways and the structural layout of the module, enabling the evaluation of thermal mismatch risks and the optimization of module design and thermal management strategies. The findings offer practical insights for battery thermal management and
Xiao, FangzhiChen, GuijieMa, ShihuHu, XiaoSong, ShujunWakale, Anil Bhaurao
Towing imposes substantial efficiency penalties on both battery-electric vehicles (BEVs) and internal combustion engine (ICE) vehicles, reducing range by 30-50%. This paper presents a proof-of-concept embedded control architecture for distributed trailer propulsion that actively regulates drawbar force to reduce towing loads. Unlike proprietary e-trailer systems requiring specialized hardware, the proposed implementation demonstrates feasibility using commercial off-the-shelf (COTS) components and open-source software. The distributed architecture employs dual Raspberry Pi 4B single-board computers communicating via ROS 2 at 20 Hz. The trailer-mounted controller executes a Simulink-generated control node coordinating load cell acquisition (HX711 ADC), motor CAN bus telemetry, and throttle commands to a 5 kW BLDC traction motor powered by a 5 kWh LiFePO4 battery pack. A vehicle-mounted controller logs OBD-II/CAN validation data. The control pipeline implements cascaded EWMA/Hampel
Joshi, GauravAdelman, IanLiu, JunDonnaway, Ruthie
Electrification is rapidly entering all vehicle classes, including light- and heavy-duty trucks designed for heavy towing capabilities. Still, the quantitative impact of towing on battery-electric vehicle (BEV) energy use and range remains under-characterized. We conducted controlled towing tests with a Ford F-150 Lightning using two trailers of different sizes and varying payloads to isolate aerodynamic and mass effects and to span the full range of towable payloads within the vehicle’s rated capacity. The vehicle was instrumented at the CAN bus level, capturing motor power, torque, speed, and related internal signals from different control modules. On-road testing consisted of repeated back-and-forth passes on level, straight road segments at set speeds focusing on highway operation, where aerodynamic drag is stronger and real-world towing use cases occur. From these data, we extracted road load equations and dynamometer coefficients for each trailer combination, then reproduced
Timermans Ladero, Inigo
With the rapid advancement of electric vehicle (EV) fast charging technology, battery thermal management faces increasingly critical challenges due to elevated heat generation and stringent safety requirements. Conventional indirect cooling methods often struggle to provide sufficient heat removal under fast charging conditions, leading to potential safety risks. Immersion cooling has emerged as a promising solution because of its superior heat dissipation capability and uniform temperature distribution. In this study, an electrochemical-thermal coupled simulation framework is developed to evaluate indirect and immersion cooling performance under high-power charging conditions. A Pseudo-two-dimensional (P2D) electrochemical EV battery model is developed in GT-SUITE and validated against vehicle charging data. An immersion cooling system is also modeled and integrated into the battery framework to allow comparison with a conventional indirect cooling system under high-power DC fast
Guo, YuyangRockstroh, TobyOezdag, ErdalHaenel, PatrickBodemann, BasilToghyani, Somayeh
Due to changed requirements compared to conventional propulsion concepts, electromobility demands new and innovative strategies for energy-efficient vehicle motion control. For example, the challenge in purely rear-wheel drive (RWD) electric vehicles (EVs) is to achieve a maximum of regenerative braking power in order to increase energy recovery and to ensure, that this does not impair the braking stability. Within this conflict between energy efficiency and braking dynamics, it is necessary to design an intelligent strategy to optimise recuperation. This paper presents such a strategy, which improves an existing approach formerly presented by the authors, but specifically optimised to overcome weaknesses. The previous approach had two major limitations: First, the efficiency map of the in-wheel machines (IWMs) was not considered. Second, there was no possibility of switching flexibly between different brake force distributions to guarantee both, maximized recovery potential and high
Mitsching, ThomasHeydrich, MariusIvanov, Valentin
Direct Current (DC) fast charging enables supply of megawatt (MW) scale DC power to the large battery systems of Heavy-Duty Electric Vehicles (HDEVs), such as electric trucks, buses, ferry and construction machinery. This contrasts with Alternating Current (AC) charging, which is limited by the capacity of the On-Board Charger (OBC) that converts AC to DC to charge the battery. In DC fast charging, however, the Electric Vehicle Supply Equipment (EVSE) delivers DC power directly to the HDEVs, bypassing the OBC. The feasibility of fast DC charging has been driven by advancements in semiconductor technology offering higher voltage and current handling capabilities as well as improvements in battery energy density. Ongoing research indicates continued growth in both semiconductor power handling and battery storage capacity, further strengthening the case for fast DC charging. Key benefits include significantly higher charging efficiency, drastically reduced charging times, and lower driver
Rahman, Md Rakib-UrDobrzynski, Daniel
Driven by the dual-carbon goals of ā€œpeak carbon emissionsā€ and ā€œcarbon neutrality,ā€ improving energy efficiency in electric construction machinery has become a key focus. This study proposes an energy-saving torque control strategy for the traction motor of electric wheel loaders, aiming to reduce drive system energy consumption. The innovation lies in coupling parameter optimization of the pedal–torque mapping and regenerative braking to enhance overall efficiency. An electric model was built using Cruise and validated against real-world V-cycle test data, showing good agreement with an average relative error of 4.08%. Based on the model, two optimized control strategies were developed and evaluated through simulations and field tests. The results showed energy savings of 7.08% and 16.18% in simulation, and 6.83% and 15.51% in tests, respectively, demonstrating the effectiveness and practical value of the proposed method.
Ming, QiaohongWang, YangyangWang, Feng
Currently, a persistent concern arises regarding the management of retired Li-ion batteries from electric vehicles (EVs). A potential solution is to repurpose these batteries for less demanding applications, such as energy storage systems. Such repurposed batteries are commonly referred to as second-life batteries (SLBs). In this work, we explore the economic feasibility of implementing SLBs in Stanford University’s EV bus charging station via previously developed technoeconomic decision support model. The model simulates battery aging behaviors across various usage conditions, optimizing the operational parameters of SLBs. The estimated lifetime is expected to be 10 years in an optimal using condition. In addition, an economic sensitivity analysis explores the influences of various factors. Furthermore, we calculate the cost savings of total $82,500 over its second lifetime, which is derived from the adoption of SLB instead of new batteries.
Zhuang, JihanChueh, WilliamOnori, SimonaBenson, Sally M.
The integration of electric vehicle charging station (EVCS) and renewable distribution generation (RDG) in the grid affects the grid voltage, power losses, and system instability in the distribution system, therefore the article presents an approach for optimal placement and sizing of EVCS and RDG using an optimization approach named as modified particle swarm optimization (MOPSO) in radial distribution network (RDN). The efficacy of the optimization approach is demonstrated under both balanced and unbalanced dynamic load conditions in the IEEE 33-bus system. The influence of EVs and RDG on the RDN is analyzed by considering the maximum possible cases, e.g., 13 different scenarios, which replicate real-world scenarios. These results are validated using DIgSILENT Power Factory Software. The proposed research also covers Techno-Economic Assessment using HOMER software, which may enhance visibility of the renewable distribution generation importance in the current scenario.
Kumar, SonuAgarwal, Ruchi
This study systematically investigates methods to enhance the fast-charging capability of lithium-ion batteries through advanced simulation. The electrochemical reaction mechanism, heat generation mechanism, and lithium plating mechanism are analyzed in detail, and an electrochemical–thermal coupled model incorporating a lithium plating sub-model is established. A hybrid parameter identification strategy, combining random search, grid search, and manual adjustment, is employed to calibrate the model across different operating conditions, thereby improving its accuracy in reproducing real battery behavior. Lithium plating is selected as the primary indicator to evaluate fast-charging performance. Based on simulation results, the effects of both operational parameters and structural parameters on lithium plating are thoroughly analyzed. The results indicate that lower charging rates, elevated charging temperatures, higher electrode porosity, and reduced tortuosity are favorable for
Zhao, PeiqiangZhan, WenweiQi, JiYi, Yong
Lithium-ion batteries represent a complex and nonlinear voltage behaviour on various time scales. Battery models are needed to analyze and estimate the battery behaviour and determine their suitability for practical applications. Battery model simulations in previous studies were mainly based on pulse charge and discharge cases. The current amplitude used in the test cases was limited, and the temperature factor of the battery model was neglected. The simulation conditions above were significantly different from those in practical applications. In this paper, an equivalent circuit model considering the temperature factor is developed to simulate the practical applications of lithium-ion batteries. Experimental tests for parameterization are applied to the commercially available 189 Ah lithium iron phosphate battery cells under a wide range of experimental conditions. The parameters are obtained through experimental tests and are used to build the equivalent circuit model of the battery
Chang, AnWang, ShengweiZhou, Kai
Lithium-ion batteries suffer from capacity degradation, lifespan attenuation, and power decline at low temperatures. Alternating-pulsed-current (APC) heating method is an effective solution for improving the low-temperature performance of batteries, but it still faces challenges in terms of low heating efficiency and energy consumption. This work proposes a pulsed-charging-current (PCC) heating method to address these issues. The effect of the PCC under various conditions, including frequency and amplitude, is investigated through experiments. According to the experimental results, the battery can be heated from -20 °C to above 7.5 °C within 15 minutes using the proposed PCC method, with a heating rate of 1.83 °C/min. Compared with the traditional APC heating method, the heating rate of the PCC method increases by 7.9%. During the 15-minute heating process, the battery capacity increased by 131.9 mAh on average, and the charging efficiency can be achieved 95% above. The proposed method
Xiao, YuechanHuang, XinrongWu, ZeZhang, YipuMeng, Jinhao
Accurate estimation of the state of health (SOH) of lithium-ion batteries is essential for ensuring the safety, reliability, and performance optimization of electric vehicles. In practical operating environments, however, data quality is often compromised by noise interference, frequent fluctuations in load conditions, and the inherently non-stationary nature of battery degradation features. These challenges reduce the effectiveness of conventional modeling approaches, which often struggle to maintain both high prediction accuracy and strong generalization capability. To address these issues, this study develops a comprehensive SOH estimation approach encompassing data quality enhancement, degradation feature extraction, and hybrid deep learning-based modeling. In the first stage, multi-stage anomaly detection techniques are applied to remove noisy or inconsistent measurements. A week-based indexing strategy is introduced to generate temporally coherent labels, ensuring that time
Wang, SijingJiao, MeiyuanHuang, WeixuanLin, YitingLiu, HonglaiLian, Cheng
As electric vehicles adoption becomes more common, power grid operators are facing new challenges in managing the unpredictable and varying energy demands in the existing electrical infrastructure. Moreover, the cost of Electric vehicle is high when compared to fuel vehicle it has limited access to charging infrastructure along with the driving range that act as a key barrier preventing the drivers from making shift to EVs. When the EV usage integrates with blockchain, it mitigates the limitation in charging station infrastructure along with the former problem discussed. The lack of trust exists between EV owners and charging station providers can be solved through secure and transparent payment processing possible by blockchain based smart contract. Building charging station on blockchain will ease the automated payment through the use of smart contract and create more efficient EV charging network. Also, the blockchain-based charging system would enable EV owners know if they are
Govindasamy, DhivyaR, Rajarajeswari
The growing awareness about sustainability and environmental concerns are accelerating the adoption of electric vehicles. They play a promising role due to their potential to significantly reduce greenhouse gas emissions, improve air quality and lessen reliance on fossil fuels. However, one of the primary concerns for potential buyers is the charging process and infrastructure. Traditional wired charging systems for electric vehicles face limitations such as user inconvenience, wear and tear of connectors and challenges in automation. A wireless electric vehicle charging offers more user-friendly, automated and contactless method by eliminating the need for physical connectors. However, wireless inductive charging suffers from relatively low efficiency due to higher energy losses. Whereas resonant coupling significantly improves efficiency by using electromagnetic resonance to transfer power more effectively over short distances. This paper mainly focuses on design and implementation
Shaik, AmjadGudipati, Ravi Sai HemanthB, Vikranth ReddyAnudeep, D B S SVarshith, Dasari
Due to the rapid transformation of EVs and the battery storage system, the battery management system (BMS) is essential to ensure optimal performance of the battery storage piles. A BMS monitors and controls parameters such as SOC, voltage, current, and temperature. A traditional BMS has a minimum support of analytics, and it’s limited to local processing. However, when the battery information is uploaded to the internet, it becomes easier to manage maintenance and track the battery’s performance from anywhere in the world. This Cloud-based system is easy and made earlier, thereby giving a system alarm before the issue becomes big. Managing many batteries at once saves a significant amount of money in places like EV charging stations and Energy Storage Systems (BESS). Software updates to the system can also be sent remotely. Also, a BMS connected to the cloud can be used to support weaker grids in an instant if it needs the reactive power support. Cloud integration of BMS with the grid
R, RajarajeswariN, KalaiarasiFrancis, Elgin Calister
This study presents the design and implementation of an advanced IoT-enabled, cloud-integrated smart parking system, engineered to address the critical challenges of urban parking management and next-generation mobility. The proposed architecture utilizes a distributed network of ultrasonic and infrared occupancy sensors, each interfaced with a NodeMCU ESP8266 microcontroller, to enable precise, real-time monitoring of individual parking spaces. Sensor data is transmitted via secure MQTT protocol to a centralized cloud platform (AWS IoT Core), where it is aggregated, timestamped, and stored in a NoSQL database for scalable, low-latency access. A key innovation of this system is the integration of artificial intelligence (AI)-based space optimization algorithms, leveraging historical occupancy patterns and predictive analytics (using LSTM neural networks) to dynamically allocate parking spaces and forecast demand. The cloud platform exposes RESTful APIs, facilitating seamless
Deepan Kumar, SadhasivamS, BalakrishnanDhayaneethi, SivajiBoobalan, SaravananAbdul Rahim, Mohamed ArshadS, ManikandanR, JamunaL, Rishi Kannan
The growing global adoption of electric vehicles (EVs) has resulted in a spike in the number of EV charging stations. As EVs have become more and more popular worldwide, a large number of EV charging stations are opening up to accommodate their demands. During grid failures, an EV charging station can also serve as a flexible load connected to the grid to balance out voltage fluctuations. An EV charging station when powered using a separate source, such as solar or wind, can function as a powerhouse, bringing electricity to the grid when it's needed. Therefore, instead of installing more equipment to sustain voltage, the current EV charging station can be efficiently used to meet the grid's needs during failures. These stations have the potential to be dynamic, grid-connected assets for sustainable cities and communities in addition to their core function of vehicle charging (SDG 11). Because of their dual purpose, they can serve as adaptable loads that reduce voltage variations during
R, UthraRangarajan, RaviD, SuchitraD, Anitha
The growing adoption of electric vehicles (EVs), particularly those utilizing High-Voltage battery systems, demands fast-charging infrastructure that ensures high efficiency and power quality. The proposed GJO algorithm is employed to optimize the control and switching parameters of the Vienna rectifier, thereby improving harmonic performance and conversion efficiency without altering the converter hardware. This paper focuses solely on control optimization of the Vienna rectifier topology and does not include DC–DC isolation or galvanic separation. Filter components are modeled with equivalent series resistance (ESR) to account for incremental losses. Simulation results demonstrate that the Golden Jackal optimization (GJO) based control reduces input current THD to 2.09%, has a power factor of 0.998, and achieves an efficiency of 98.53%, representing a fractional but consistent improvement over conventional control methods such as SSA, ALO, and PSO. These findings highlight the
R, Mohammed AbdullahN, Kalaiarasi
The proliferation of wireless charging technology in electric vehicles (EVs) introduces novel cybersecurity challenges that require comprehensive threat analysis and resilient design strategies. This paper presents a proactive framework for assessing and mitigating cybersecurity risks in wireless charger Electronic Control Units (ECUs), addressing the unique vulnerabilities inherent in electromagnetic power transfer systems. Through systematic threat modeling, vulnerability assessment, and the development of defense-in-depth strategies, this research establishes design principles for creating robust wireless charging ecosystems resistant to cyber threats. The proposed framework integrates hardware security modules, encrypted communication protocols, and adaptive threat detection mechanisms to ensure operational integrity while maintaining charging efficiency. Experimental validation demonstrates the effectiveness of the proposed security measures in preventing unauthorized access, data
Uthaman, SreekumarMulay, Abhijit BGadekar, Pundlik
This comprehensive research presents an in-depth analysis of communication protocols essential for implementing fast charging systems in India's rapidly expanding electric two-wheeler and three-wheeler market. As India witnesses unprecedented growth in electric mobility, with two-wheelers representing over 95% of current EV sales, the establishment of standardized, secure, and efficient charging protocols becomes paramount for widespread adoption. This study examines the current landscape of AC charging methodologies, evaluates the technical and economic feasibility of DC fast charging implementation, and provides detailed comparative analysis of existing international standards including IS 17017-25, IS 17017-31, ChaoJi, and CCS 2.0. The research concludes with strategic recommendations for developing cyber-secure, cost-effective charging infrastructure specifically tailored to meet India's unique market requirements and operational constraints.
Uthaman, SreekumarMulay, Abhijit B
State Transport Units (STUs) are increasingly using electric buses (EVs) as a result of India's quick shift to sustainable mobility. Although there are many operational and environmental benefits to this development, like lower fuel prices, fewer greenhouse gas emissions, and quieter urban transportation, there are also serious cybersecurity dangers. The attack surface for potential cyber threats is expanded by the integration of connected technologies, such as cloud-based fleet management, real-time monitoring, and vehicle telematics. Although these systems make fleet operations smarter and more efficient, they are intrinsically susceptible to remote manipulation, data breaches, and unwanted access. This study looks on cybersecurity flaws unique to connected passenger electric vehicles (EVs) that run on India's public transit system. Electric vehicle supply equipment (EVSE), telematics control units (TCUs), over-the-air (OTA) update systems, and in-car networks (such as the Controller
Mokhare, Devendra Ashok
The rapid expansion of electric vehicle (EV) charging infrastructure introduces complex cybersecurity challenges across hardware, software, network, and cloud layers. This review paper synthesizes existing research, standards, and documented incidents to identify critical vulnerabilities and propose layered mitigation strategies. We present a structured threat taxonomy based on the STRIDE model, enriched with real-world attack vectors and mapped to mitigation controls. Our analysis spans physical tampering, insecure firmware updates, protocol-level flaws in OCPP and ISO 15118, and cloud misconfigurations. While prior studies often focus on isolated domains, this work unifies fragmented insights into a cohesive framework. We highlight gaps in current literature, such as inconsistent adoption of secure protocols and limited validation of EVSE identity formats. By aligning threats with industry standards (SAE J3061, NIST CSF, IEC 62443) and scoring risks using CVSS v3.1, we offer a
Aggarwal, AkshitGupta, SaurabhSirohi, KapilArisetty, VenkateshChatterjee, Avik
This paper introduces a modeling and simulation methodology for transient analysis of surge protective devices (SPDs) for electric vehicle charging system (EVCS) application. The suggested Surge Protective Device topology is to shield the EV power electronics such as on board charger from surge events generated by the grid during charging, with implementation on the grid-EV interface. A new surge protection circuit is designed to suppress transient overvoltages, with its performance evaluated through simulation. The SPD is evaluated in SPICE simulator in the time domain, including its nonlinear spark over characteristics along with its resistive, capacitive and inductive effects. Equivalent circuit is developed and evaluated by simulation under typical surge conditions. The outcomes prove the topology to be effective in clamping voltage, reducing energy transfer to the EV side, and achieving surge event detection. The contribution of this work lies in the establishment of dependable
CHANCHAL, Kumar Prem ChandraKulkarni, SwanandRajaram Joshi, SanjayPatil, Sagar
This study aimed to develop a thermally conductive TPE mat and assess its performance in comparison to an existing antiskid rubber mat, specifically evaluating its impact on wireless charger efficiency. Moreover, morphological and thermal analyses were conducted to establish a correlation between the material behaviours of the new and current thermally conductive antiskid mats. The process of developing the thermally conductive TPE involved utilizing a two-roll mill followed by compression moulding to achieve a 2D sheet shape. Notably, the thermally conductive mat demonstrated a consistent enhancement in charging efficiency over the conventional antiskid mat. To examine the thermal characteristics, thermal characterization techniques including DSC and TGA were employed for both the existing and newly developed mats. FTIR spectroscopy was also utilized to confirm the presence of organic functional groups within the mat. The morphological analysis of the fillers used to enhance thermal
Naikwadi, Amol TarachandMali, ManojPatil, BhushanTata, Srikanth
In its conventional form, dynamometers typically provide a fixed architecture for measuring torque, speed, and power, with their scope primarily centered on these parameters and only limited emphasis on capturing aggregated real-time performance factors such as battery load and energy flow across the diverse range of emerging electric vehicle (EV) powertrain architectures. The objective of this work is to develop a valid, appropriate, scalable modular test framework that combines a real-time virtual twin of a compact physical dynamometer with world leading real-time mechanical and energy parameters/attributes useful for its virtual validation, as well as the evaluation of other unknown parameters that respectively span iterations of hybrid and electric vehicle configurations, ultimately allowing the assessment of multiple chassis without having to modify the physical testing facility's test bench. This integration enables a blended approach, using a live data source for now, providing
Kumar, AkhileshV, Yashvati
In high-performance charging systems, managing higher currents is crucial for efficient battery charging. Elevated battery temperature is the main challenge for limiting the duration and effectiveness of high-current charging. Our proposal of control system addresses these barriers by optimizing charging time by maintaining optimal temperature ranges for the battery. This is achieved through innovative preconditioning solutions that are incorporated with active Battery cooling configurations. Our system features a unique preconditioning approach with dedicated active cooling circuit for the battery which will provide cooling to battery even though cabin HVAC (Heat Ventilation & Air-conditioning unit) is switched off. The active liquid cooling system ensures effective temperature management without additional energy consumption, while the dedicated Battery active liquid cooling system provides enhanced cooling capabilities for more demanding scenarios and preconditioning. By integrating
Badgujar, Pankaj RavindraBhosale, SubhashDave, Rajeev
Accurate range estimation in battery electric vehicles (BEVs) is essential for optimizing performance, energy efficiency, and customer expectations. This study investigates the discrepancies between physical test data and simulation predictions for the BEV model. A detailed range delta analysis identifies key contributors to the observed deviations, including regenerative braking inefficiencies, increased propulsion demand, auxiliary loads, and estimated drivetrain losses within the Electric Drive Module (EDM) during traction and regen. Results indicate that the test vehicle exhibits lower regenerative braking efficiency, higher traction forces and lower regen energy than predicted by simulations, primarily due to EDM inefficiencies and friction brake usage during regeneration. The study underscores the importance of refining simulation methodologies by integrating real-world, test based EDM loss maps to improve accuracy and better align predictive models with actual vehicle
Mahajan, PrasadKesarkar, SidheshAli, Shoaib
The invention tackles the main drawback of traditional electric vehicle charge ports which use Vehicle Control Unit (VCU) communication intensively and tend to have separate actuators to fulfill the locking function and requirements. These existing systems do not only limit autonomous operation of the charging lid in ignition-off condition but they also add mechanical complexity and packaging space, as well. To overcome these limitations, this research work introduces a Smart Charge Port Housing (CPH), which combines a rotary actuator with an onboard microcontroller and single shaft self-locking device, which allows intelligent and autonomous control of the flaps without relying on vehicle wide control networks. The actuator can remember the last position that the charging lid was in so it can be operated even while the VCU is in the inactive state. The integrated self-locking functionality is achieved by using a specially designed hinge shaft that allows a certain free play for
Mohunta, SanjayKhadake, Sagar
This paper presents the design, implementation, and evaluation of a high-efficiency Phase-Shifted Full-Bridge (PSFB) DC-DC converter utilizing Silicon Carbide (SiC) MOSFETs for low-voltage (LV) battery charging in electric vehicle (EV) applications. The converter operates with Peak Current Mode Control (PCMC), enhanced by a digitally implemented slope compensation technique to ensure control loop stability, counter subharmonic oscillations and accurate current regulation across a wide load range. The use of SiC devices enables high switching frequencies operation with reduced conduction losses, contributing to improved efficiency and power density of converter. The hardware design utilizes a planar transformer with shim inductance to enable Zero Voltage Switching (ZVS) of the primary switches, thereby reducing switching losses and mitigating transformer flux imbalance. The secondary stage employs diode rectification, while the overall PCB layout is optimized to minimize parasitics and
Kumar, MayankDeosarkar, PankajTayade, NikhilInamdar, Sumer
Precise estimation of power metrics like active power, reactive power and apparent power is mandatory for effective control and monitoring of three phase power systems. On the other hand there might be challenges like waveform distortion, noisy signals and unbalanced load circumstances. traditional methods may not always provide accuracy in such an environment thus to address that in this study, we are using cross correlation and zero crossing methods to estimate power parameters of a three phase system. We are using these signal processing techniques to find phase angle, which in turn determines all other power parameters like active power, reactive power, apparent power, power factor. While Cross correlation tracks both the signals at different time lags and evaluate similarity between both the signals, zero crossing point approach identifies some particular locations where signal crosses zero axis. This analysis can be used in various applications such as power parameters monitoring
Panchal, Sanjivani VishwanathRoy, Sandipan
In recent years, the automotive industry has been looking into alternatives for conventional vehicles to promote a sustainable transportation future having a lesser carbon footprint. Electric Vehicles (EV) are a promising choice as they produce zero tail pipe emissions. However, even with the demand for EVs increasing, the charging infrastructure is still a concern, which leads to range anxiety. This necessitates the judicious use of battery charge and reduce the energy wastage occurring at any point. In EVs, regenerative braking is an additional option which helps in recuperating the battery energy during vehicle deceleration. The amount of energy recuperated mainly depends on the current State of Charge (SoC) of the battery and the battery temperature. Typically, the amount of recuperable energy reduces as the current SoC moves closer to 100%. Once this limit is reached, the excess energy available for recuperation is discharged through the brake resistor/pads. This paper proposes a
Barik, MadhusmitaS, SethuramanAruljothi, Sathishkumar
India's electric 2-wheeler (E2W) market has witnessed fast growth, driven by lucrative government policies. The two-wheeler segment dominates the Indian automotive market, accounting for the largest share of total sales. Consequently, the manufacturers of 2-wheelers are developing new electric vehicles (EV) tailored for the Indian market. However, the Indian EV market has witnessed multiple fire accidents in recent years, raising safety concerns among consumers and industry stakeholders. These incidents highlight key weakness in battery thermal management systems (BTMS), particularly during charging. Most existing E2W BTMS relies on passive (natural) air cooling, which has been associated with fire incidents due to its inefficiency in heat dissipation, particularly during charging in India's high-temperature environment. Therefore, it is imperative to build thermally viable and economical BTMS for the growing E2W vehicles with fast charging capability. FEV is actively developing the
Raut, AnkitHiremath, Vinodkumar SEmran, AshrafGarg, ShivamBerry, Sushil
Electric Vehicles and Plug-in Hybrids alleviate the energy crisis but pose a unique challenge for vehicle dynamics. Though significant developments in motor control strategy and energy density management are evolving, we face significant challenges in torque management, with several ADAS features being an integral part of the EVs/xHEVs. It demands high-fidelity physical and control model exchanges between electric chassis, ride-handling, tire modelling, steering assist, powertrain, and validation using a 0D–1D platform. This paper explicates a unified strategy for improving overall vehicle performance by intelligently distributing and coordinating drive torque to enhance traction, stability, and drivability across diverse operating conditions through co-simulation. The co-simulation platform includes physical models in AMESIM, and control strategies integrated in MATLAB/Simulink. The platform features comprehensive representations of digital vehicles that require detailed modelling of
Eruva, PatrickxavierSarapalli Ramachandran, RaghuveeranChougule, SourabhNatanamani-Pillai, Siva SubramanianScheider, ClementLeclerc, CedricNatarajasundaram, Balasubramanian
Electric mobility is no longer a distant vision, it is a global imperative in the journey of fight against the climate change and the urban pollution. Yet, despite of explosive growth in the electric vehicle adoptions, a major bottleneck remains which is efficient and convenient charging. The current reliance on physical plug in charging station creates inconvenient, time consuming experience and also faces significant technical and economic challenges those threaten to stall the smooth clean transportation revolution. Without innovation in how we recharge our vehicle the promise of electric mobility appears under threat which is undermined by less efficient, less compatible, and infrastructure hurdles. Wireless charging technology stand out as the game changing breakthrough poised to tackle these all critical problems head on. By enabling the effortless, cable-free charging system across the wide spectrum of electric vehicles, from the personal cars to the public transport fleets and
Jain, GauravPremlal, PPathak, RahulGore, Pandurang
The rapid advancement of electric vehicle (EV) technology has created a demand for reliable and Thermal - efficient electronic components for power electronics and control systems on printed circuit boards (PCBs). The research looks at the overall simulation and study of a PCB for Electric Vehicles, including how it handles heat, stress, and reliability in real working conditions like considering casing (Heat Sink) in which PCB is held, into the simulation. We have used numerical based methods (reliability), Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) methods to simulate heat performance looking at steady-state and changing load profiles common in EV powertrains. We ran structural and thermal simulations to check the PCB's toughness against heat expansion and shaking loads often seen in cars. We also did a reliability check looking at heat cycling life for PCB components, and possible ways it could break to guess long-term toughness. The results show critical
Kanbarkar, Suraj OmanaDeore, UdayPatil, NishikantNayak, Shibabrata
A mobile wireless charger is a device that charge a smartphone or other compatible gadgets without the need for physical cables. Principle of wireless mobile charger system based on inductive coupling phenomena. The main objective of this paper aims to address the challenge of packaging wireless mobile charger in peculiar door trim profile keeping overall functionality and aesthetic appearance of door trim intact. This paper deals with integration of a wireless charging system within the door trim of a vehicle to provide convenience and advanced functionality. The objective is to pack a wireless charger in door trim meeting the ergonomic target and equilibrium state stability while maintaining sleek and minimalist design of the door trim. The study focuses on innovative packaging solutions related to space optimization in door despite multiple challenges involved. Major challenge lies in packing the unit amidst complex mechanisms such as window regulators, speakers, structural
Palyal, NikitaD, GowthamBhaskararao, PathivadaKumarasamy, Raj GaneshBornare, Harshad
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