Search Results (3,101)

This paper presents an integrated validation framework for EV taxi charging-hub plans that combines spatial accessibility, grid deployability, and operational performance. Candidate hub configurations are first generated through a demand-weighted p-median model based on 175 taxi stands and 2825 cooperative members in Belém, Brazil. The assigned demand is then translated into charger requirements through stochastic sizing, and the resulting infrastructure is screened against the available headroom of 12,905 medium-voltage transformers. Finally, the selected solution is evaluated through an Erlang-C queueing model under peak-demand concentration. The final plan, obtained with 14 hubs, achieved a weighted mean distance of 0.724 km and a weighted P95 distance of 1.488 km, while requiring 46 chargers and 2610 kW of installed capacity. Of these, 45 chargers were successfully allocated in the grid-screening stage, corresponding to a placement rate of 97.83%. Full article

This paper presents a comprehensive methodology for evaluating the flexibility potential of Electric Vehicle (EV) charging infrastructures from the perspective of a Charge Point Operator (CPO). The proposed framework is general and applicable to different types of charging infrastructures, provided that a set of operational assumptions is satisfied. These include unidirectional smart charging (V1G), AC charging sessions, preservation of user energy delivery when providing flexibility, and explicit modeling of rebound effects induced by temporal load shifting, requiring subsequent recovery of the shifted energy. The methodology is then applied to a real-world workplace charging facility to quantify the amount and temporal distribution of flexibility under different baseline charging strategies and levels of on-site photovoltaic integration. The analysis shows that a significant share of daily energy demand (i.e., between 20% and 36%) can be made available for flexibility services within the considered assumptions. Furthermore, the results highlight a strong operating cost trade-off between local optimization strategies and participation in system-level flexibility markets in the considered case study. Full article

Accurate online tracking of state of charge (SOC) inconsistency in lithium-ion battery packs is essential for safety. It is equally critical for effective battery management in real-world operation. To achieve robust performance in dynamic battery environments characterized by temperature fluctuations and cell aging, a method combining enhanced Rime optimized-unscented particle filter (ERIME-UPF) with cubature smooth variable structure filter-varying boundary layer (CSVSF-VBL) is proposed. The cell mean-difference model is used to simulate the behavior characteristics of the battery module, including the hysteresis effect dynamic migration model, and the Rint model. First, module SOC is estimated using an ERIME-UPF, which adaptively adjusts the noise covariances of UPF via the enhanced RIME optimizer. Simultaneously, CSVSF-VBL employs the Rint model to estimate cell SOC inconsistencies, incorporating capacity and internal resistance coefficients into the second-order performance chattering to better capture cell inconsistency. Experiments focus on LiFePO₄ batteries under various inconsistencies, temperature, and aging states. The results show that ERIME-UPF achieves an average mean absolute error (MAE) of 0.33% for module SOC estimation, while CSVSF-VBL achieves a peak MAE of 3.28% for cell SOC estimation. Demonstrating superior accuracy and robustness in tracking SOC inconsistency under dynamic and degraded operating conditions. Full article

This work presents the results of an on-road test campaign on an aged mid-size battery electric vehicle. After a full charge, the vehicle was completely discharged by driving on the road, with different routes (combining speeds and road slopes) and payloads. The resulting driving range and discharged battery energy were measured. The results are compared with those obtained from previous laboratory test campaigns on a chassis dynamometer driving at constant speed or with the standardised testing protocols according to the WLTP. Considerations of the influence of environmental and route conditions on the usable battery energy during the on-road test are made. The new concept of virtual distance related to V2X applications is presented based on the UN GTR No. 22 dealing with in-vehicle battery durability. This is a new concept introduced to account for the additional ageing caused by battery cycling due to applications other than driving or charging. Full article

CO₂ emissions are rapidly rising with new records, and the transport sector is considerably contributing to GHG emissions. The critical transition towards electrification and sustainable development demands a radical change in the transport industry. One of many solutions is to analyze the environmental benefits of optimized vehicle production and recycling of the vehicle components after their usable life to reduce dependency on limited raw materials. The electric motor is one of the most crucial powertrain components, yet studies on the overall ecological profile of production and the end of its usable life are limited. This study examines the life cycle assessment (LCA) impacts of electric motors used in passenger cars and the potential recycling of their materials. The analysis covers the production and recycling of components, crucial elements, and permanent magnets. The results show that housing and rotor production have the highest impacts, mainly due to the presence of steel, aluminum and permanent magnets. The findings discuss e-motor recycling innovations, state-of-the-art methods and emission-reduction potentials of recycling. This paper also covers the understanding that a significant transformation to optimize the resource consumption in the manufacturing of crucial vehicle powertrain components and reduce waste after end-of-life could bring combined ecological advantages. Full article

The performance attributes of a heterogeneous multi-battery pack system significantly impact the electric vehicle's performance. This study aims to investigate the power reduction and energy utilization phenomena in heterogeneous battery pack configurations that arise due to an uneven current split, focusing on defining the power ability curves and usable energy for the mixed system. A Multiphysics-based system model has been developed to investigate the factors contributing to power loss and usable energy when the aged packs are mixed with fresh packs. Different methods, viz., scaled, aged, and interpolation, are proposed to estimate the power retention curves for one and two fresh packs mixing into the homogeneous system. Also, energy evaluation helps in identifying the impact on vehicle range, which is an important attribute of vehicle performance. Altogether, having power ability curves and usable battery energy (UBE) for a heterogeneous multi-pack system helps in defining the decision-making strategies for the refurbishment of ESS during replacement and maintenance activities in EVs. Some strategies are introduced at the end using aged and scaled methods to conduct the most conservative power estimations while pack mixing. Energy evaluation is performed at the ESS level, highlighting the impact of fresh pack on the aged system usable energy. Full article

Vehicle-to-Grid (V2G) is increasingly recognized as a promising source of flexibility for low-carbon energy systems, yet its deployment remains limited in practice. While previous research has largely focused on technical feasibility and market integration, less attention has been paid to V2G as a multi-actor service system. This study addresses that gap by applying a service design perspective to the co-development of a V2G service blueprint in the Swedish context. The research was conducted through an exploratory multi-stakeholder co-design process. The resulting blueprint maps customer actions, frontstage and backstage processes, stakeholder interactions, and communication flows across the V2G service lifecycle. The study identifies several service-level challenges related to onboarding, coordination, pre-qualification, contractual complexity, and user-facing value communication. The findings show how service blueprinting can support the structuring, analysis, and early-stage design of V2G services, while also highlighting the need for further validation in pilot implementation and across different regulatory contexts. Full article

This study assesses the impact of regenerative braking on lithium-ion battery aging and operational efficiency of lithium-ion batteries in urban electric buses using a Rainflow-based cycle-counting framework. A previously developed simulation platform based on Energetic Macroscopic Representation (EMR) is employed to reproduce realistic daily driving cycles. Battery degradation is quantified by combining the Rainflow Counting Method with Miner’s Rule, enabling cumulative damage assessment across different depth of discharge (DoD) levels and regenerative braking intensities, k_br. Four representative cycling profiles—fixed 50%, 60%, and 70% DoD and a variable mixed-use scenario—were simulated under regenerative braking intensities ranging from 0% to 100%. Results indicate that regenerative braking extends average battery lifespan by approximately 0.9 years while increasing daily driving range by around 6 km. Profiles with lower DoD values, particularly when combined with moderate regenerative braking (k_br ≈ 0.3), achieved the most favourable balance between cycle induced degradation and energy recovery. Although higher DoD scenarios deliver greater mileage gains, they also accelerate capacity fade. The variable cycling profile demonstrated robust and consistent performance, highlighting the benefits of route and load variability. Additionally, lifetime mileage analysis demonstrates that intermediate DoD levels combined with regenerative braking maximize cumulative energy throughput while preserving service life. Overall, the proposed methodology offers a computationally efficient and practically applicable approach for battery life assessment under dynamic operating conditions, offering valuable insights for optimizing energy management strategies and electric bus fleet operations. Full article

The second-life application of vehicle batteries is getting attention as millions of battery systems, modules, or cells are going to enter the market in the coming decade. The performance uncertainty with or without historical knowledge of the batteries’ vehicle usage is a concern. Moreover, detailed studies on second-life battery cell behavior is sparse and an improved understanding is required for reuse/repurpose. In this work, two second-life battery packs are dismantled, and the extracted prismatic and pouch Nickel–Manganese–Cobalt (NMC) cells with 141 Ah and 65 Ah, respectively, are extensively investigated to understand the second-life degradation behavior. The one-and-a-half-year-long test campaign has followed dedicated suitable stationary test matrices, generating a valuable dataset. The aging dataset is then filtered with the most correlated features via Pearson correlation analysis (PCA) and used to train different machine learning algorithms, resulting in a root-mean-square-error (RMSE) of 0.065 and 0.109 for prismatic and pouch cells, respectively, with the best-performing ElasticNet model validated against real-life stationary profiles. The developed framework is suitable for edge computation where the SoH could be evaluated online, facilitating state-based performance and lifetime extension. Full article

The SAE J2841 utility factor (UF) estimates the fraction of driving expected to occur in charge-depleting (CD) mode for plug-in hybrid electric vehicles. Emerging in-use data suggest that real-world electric usage is lower than assumed, motivating a reassessment of how charging behavior and related factors should be incorporated into the UF curve. Using trip-level data from approximately 1000 PHEVs observed over one year, we develop a charging model that captures both population-level heterogeneity in charging frequency and day-to-day characteristic temporal patterns in individual charging. The charging behavior modeling is applied to NHTS driving data to generate UF curves spanning 5 to 200 miles (8 to 322 km) of CD range. When key behavioral features are included, the resulting CD driving fractions align closely with industry-provided data. Sensitivity analysis indicates that the assumed share of habitual non-chargers is among the most influential parameters affecting the gap between the original UF and in-use data. Multiple modeling approaches were used to explore the problem and compare results, including machine learning, logistic regression, and parametric methods. Additional factors such as blended CD operation and temperature effects are discussed within a modular framework for refining J2841. These findings inform ongoing discussions on PHEV utility representation in analytical and regulatory contexts. Full article

To address the issue of vehicle instability and veering during braking when a single wheel fails in an electric vehicle’s electromechanical braking (EMB) system, an integrated application-oriented control framework based on adaptive sliding mode control (ASMC) is proposed. To address the shortcomings of SMC—such as difficulty in suppressing oscillations and the high workload associated with parameter tuning—a novel composite reaching law function was designed, and the TD3 algorithm was employed to optimize the sliding mode control parameters. When a failure in the EMB system is detected, the upper-layer control uses an improved ASMC algorithm to calculate the vehicle’s additional yaw moment. The lower-layer control employs an optimal control algorithm to distribute braking force, taking into account braking intensity, yaw moment, and tire utilization. This approach is integrated with sliding mode steering control to enhance vehicle stability during braking. To meet the driver’s braking requirements, a backpropagation (BP) neural network is first employed to identify braking intent. Based on this, the additional yaw moment is calculated by the upper-layer controller, and the brake force distribution is optimized through the lower-layer controller, thereby improving the vehicle’s stability. Through co-simulation analysis using Simulink-2024a and CarSim-2019.1, the results show that, compared to traditional algorithms, the proposed hierarchical control strategy reduced the maximum sideslip angle by 51.4%, decreased the maximum yaw rate by 47.2%, and reduced the maximum lateral offset by 45.6%. This control strategy enables enhanced stability across various braking intensity conditions. Full article

Electric vehicles are becoming more common daily because countries are moving towards net-zero emissions. Different generations of NMC battery cells are used for EV applications. This work investigates the degradation behavior of high-energy 75 Ah prismatic NMC631 lithium-ion cells using a combined incremental capacity analysis (ICA) and electrochemical impedance spectroscopy (EIS) framework under different conditions. Cells are cycled at an identical C-rates and depths of discharge (DoD), and at different temperatures to systematically evaluate the impact of temperature on electrochemical aging. ICA results revealed that cells cycled at low temperatures maintain stable peaks and a high SoH (>90%) after completing 1600 full equivalent cycles (FECs). EIS analysis confirms the distinct impedance evolution patterns. Degradation mode analysis is performed using the ICA, and EIS highlights the combined evolution of conductivity loss, loss of lithium inventory, and loss of active material. It also highlights different degradation path trajectories under identical operating conditions stem from the progressive amplification of internal cell heterogeneities during aging. The results demonstrate that combining ICA and EIS provides complementary insights into degradation evolution and enables clear differentiation between gradual aging and sudden failure pathways in high-energy NMC cells. Full article