World Electr. Veh. J., Volume 13, Issue 8 (August 2022) – 28 articles

Pedestrians are important traffic participants and prediction of pedestrian crossing intention can help reduce pedestrian–vehicle collisions. For the problem of predicting an individual pedestrian’s action where there is crossing potential, a pedestrian crossing intention prediction method that considers multi-feature fusion is proposed in this study, which integrates information affecting pedestrians’ actions, such as pedestrian action and traffic environment. This study is based on the BPI dataset for training and validation, and the test results show that the model has good data fitting and generalization ability; the test set has good prediction accuracy of 89.5% in the model, with an AUC of 0.992. In the specific scenario, the method proposed in this study can predict pedestrian crossing intention when the longitudinal relative distance between a pedestrian and vehicle is about 20 m and about 0.6 s before the pedestrian crossing, which can provide useful information for decision making in intelligent vehicles. Full article

This paper presents a bibliometric analysis of battery state estimation in electric vehicles. In this paper, a quick study is performed on the top global research contributors, funding agencies, and affiliate universities or institutes performing research on this topic while also finding the top keyword searches and top authors based on the most citations in the field of electric vehicles. Trend analysis is done by using the SCOPUS and Web of Science (WOS) databases (DB) from the period of 2000 to 2021. Battery state estimation plays a major role in the battery present state based on past experience. Battery available charge and health knowledge is a must for range estimation and helps us acknowledge if a battery is in useful condition or needs maintenance or replacement. A total of 136 documents in SCOPUS and 1311 documents in Web of Science were analyzed. Through this bibliometric analysis, we learn the top authors, country, publication journal, citation, funding agency, leading documents, research gap, and future trends in this research direction. The author Xiong Rui has the most publications, and he is working at the Beijing Institute of Technology, China. The most common institution is the Beijing Institute of Technology, and China is the most highly contributing country in this research. Most of the publications are conference types in SCOPUS DB and article types in WOS DB. The National Natural Science Foundation of China provides the most funding. The journal Energies has the most publications related to this field. The most cited works are by the authors M.A. Hannan and L.G. Lu in SCOPUS and WOS DB, respectively. A statistical analysis of the top ten countries’ productivity results is also discussed. Full article

These memoirs about Walter Lachenmeier (1945–2022) concentrate on his activities as head of the engineering sciences group of the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG), for which he worked from 1977 to 2007, and his following scientific activities in electric vehicle research and development, including a review of his patents in this area, which encompass topics from enhancement of the performance and lifetime of lithium-ion batteries, their arrangement, connection and configuration, as well as efficiency increase in supply and storage of energy. Full article

One of the biggest problems associated with vehicles that use internal combustion engines is that they cause elevated levels of pollution in the places they travel through, especially if they cause congestion. However, it is not only the level, but also probably the concentration of gases emitted by internal combustion engines in the places where they move around that is particularly lethal. Can the road transport sector’s electrification mitigate premature deaths from outdoor air pollution? Our main hypothesis is that replacing internal combustion engine vehicles with electrical ones contributes to mitigating people’s exposure to high concentrations of air pollution. To answer the research question, a panel of 29 European countries, from 2010 to 2020, using the method of moments quantile regression and ordinary least squares, was examined. Results support the concept that economic growth, renewable energy consumption, and electric vehicles in all quantiles have a negative impact on premature mortality due to air pollution. These impacts are higher on premature mortality in lower quantiles, but gradually decrease with increasing quantile levels. The results also reveal that methane emissions, in all quantiles except 10th, have a negative effect on premature mortality. Nitrous oxide emissions positively impact premature mortality in all quantiles except the 10th, and this impact increases at high quantiles. Fine particulate matter positively impacts premature mortality in all quantiles, with the same at all levels. The ordinary least squares, used as a robustness check, confirm that economic growth, renewable energy consumption, and methane emissions have reduced impacts on premature mortality due to outdoor air pollution. However, nitrous oxide emissions and fine particulate matter increase premature mortality. These results reinforce the importance of policymakers implementing policies for road electrification. Full article

Additive manufacturing (AM) offers the possibility to produce components in a resource-efficient and environmentally friendly way. AM can also be used to optimise the design of components in mechanical and physical terms. In this way, functionally integrated, lightweight, highly efficient, and innovative components can be manufactured with the help of additive manufacturing in terms of Industry 4.0. Furthermore, requirements in the automotive industry for drivetrain components are increasingly being trimmed in the direction of efficiency and environmental protection. Especially in electromobility, the topic of green efficiency is an essential component. Exhaust emission legislation and driving profiles for evaluating vehicles are becoming increasingly detailed. This offers the potential to apply the advantages of AM to vehicle types such as conventional, utility vehicles, and nonroad mobile machinery (NRMM), independent of the electrical drivetrain technology (hybrid or fully electrical). AM also allows for us to produce optimally adapted components to the respective requirements and use cases. In this review, the intersections of AM and electromobility are illuminated, showing which solutions and visions are already available for the different vehicle types on the market and which solutions are being scientifically researched. Furthermore, the potential and existing deficit of AM in the field of electromobility are shown. Lastly, new and innovative solutions are presented and classified according to their advantages and disadvantages. Full article

The full implementation of electric public transport is a key step for the transport industry to move toward electrification and achieve carbon neutrality. However, in the face of time-varying demands and high-quality service requirements, traditional transit systems are difficult to ascend as the preferred mode of travel due to the constraints of fixed vehicle capacity and multiline transfers. With the advent of modular vehicle technology, it is becoming more realistic to develop an entirely new transportation system based on electric modular vehicles (EMVs). This study proposes a novel intelligent platoon transit system (IPTS), and its overall concept and operating mode are elaborated at a strategic level. In particular, the electrical, modular, and autonomous platoon transit system should be designed to achieve adaptive adjustment of capacity and possible en route transfers, which significantly improves the convenience, flexibility, and economy of public transport. We also design three application scenarios with varying demands during multistage development to bridge the gap in traditional buses. The key issues and case applicability of the three scenarios are discussed. Full article

The need for a more flexible usage of power is increasing due to the electrification of new sectors in society combined with larger amounts of integrated intermittent electricity production in the power system. Among other cities, Uppsala in Sweden is undergoing an accelerated transition of its vehicle fleet from fossil combustion engines to electrical vehicles. To meet the requirements of the transforming mobility infrastructure, Uppsala municipality has, in collaboration with Uppsala University, built a full-scale commercial electrical vehicle parking garage equipped with a battery storage and photovoltaic system. This paper presents the current hardware topology of the parking garage, a neural network for day-ahead predictions of the parking garage’s load profile, and a simulation model in MATLAB using rule-based peak shaving control. The created neural network was trained on data from 2021 and its performance was evaluated using data from 2022. The performance of the rule-based peak shaving control was evaluated using the predicted load demand and photovoltaic data collected for the parking garage. The aim of this paper is to test a prediction model and peak shaving strategy that could be implemented in practice on-site at the parking garage. The created neural network has a linear regression index of 0.61, which proved to yield a satisfying result when used in the rule-based peak shaving control with the parking garage’s 60 kW/137 kWh battery system. The peak shaving model was able to reduce the highest load demand peak of 117 kW by 38.6% using the forecast of a neural network. Full article

In this study, a framework regarding park and ride facilities is presented and demonstrated to evaluate different approaches of charging concepts. The innovation in this study is that the framework can be used to evaluate arbitrary conductive charging concepts on a detailed level and on the basis of real usage data. Thus, the results can be broken down to the level of individual charging events and charging points. Among other factors, the study considers the expected growth in electric vehicles, the construction and operating costs for the investigated charging infrastructure, and the impact of heterogeneous electric vehicle fleets with different vehicle-specific charging powers. Since both technological and economic perspectives are considered in the framework, the study is relevant for all decision makers involved in the development and operation of charging infrastructure. The results in the investigated case of park and ride facilities show a high potential for cost-efficient low-power charging concepts. Thus, significantly higher energy volumes could be transmitted and better economic results could be achieved by the investigated low-power approaches. Especially for heterogeneous electric vehicle fleets, the number of available charging points appears to be more important than the charging power of the individual charging points in this case. Full article

In this paper we investigate differences between groups of Norwegian electric vehicle owners, sorted by their adoption level. The grouping is based on adoption theory and the share of battery electric vehicles in new car sales numbers. We investigate Norwegian adopters’ preferences, values, and motivations for choosing a battery electric vehicle. The main data source is a yearly survey between 2015 and 2020 amongst Norwegian electric vehicle drivers. The motivation of the study is to reveal different choices by the adopter groups, contributing to policy recommendations and incentives for other countries. However, the Norwegian case might be a special one, having economic advantages which many other countries do not have access to. We assess the validity of the results and policy recommendations by analysing the results of a survey amongst the Nordic countries on investment choices concerning battery electric vehicles. Full article

In this work, a numerical optimisation process is applied to improve the fluid dynamical aspect of an innovative direct liquid cooling strategy for lithium-ion–based HEV/EV. First, the thermofluidic numerical model of the battery cell defined by means of CFD computational tools was validated with experimental tests. Then, a comparison between different flow patterns was developed to analyse the influence of the fluid distribution geometry. Finally, a parametric multi-objective optimisation process was implemented arranged by a two-level full factorial design. Considering as input variables the height of the fluid, the number of cooling channels, the number of distributors, and the flow rate, the optimal relationship between the thermal performance of the battery cell, the volumetric energy density of the system, and the power consumption of the strategy was obtained. As a result, the energy density of the system was maximised, and the power consumption was reduced while keeping the cell temperature within the optimal range. Full article

An accurate state-of-health (SOH) estimation is vital to guarantee the safety and reliability of a lithium-ion battery management system. In application, the electrical vehicles generally start charging when the battery is at a non-zero state of charge (SOC), which will influence the charging current, voltage and duration, greatly hindering many traditional health features to estimate the SOH. However, the constant voltage charging phase is not limited by the previous non-zero SOC starting charge. In order to overcome the difficulty, a method of estimating the battery SOH based on the information entropy of battery currents of the constant voltage charging phase and charging duration is proposed. Firstly, the time series of charging current data from the constant voltage phase are measured, and then the information entropy of battery currents and charging time are calculated as new indicators. The penalty coefficient and width factor of a support vector machine (SVM) improved by the sparrow search algorithm is utilized to establish the underlying mapping relationships between the current entropy, charging duration and battery SOH. Additionally, the results indicate the adaptability and effectiveness of the proposed approach for a battery pack and cell SOH estimation. Full article

The optimal design of a super highspeed flywheel rotor could improve flywheel battery energy density. The improvement of flywheel battery energy density could enhance the performance of the flywheel lithium battery composite energy storage system. However, there are still many problems in the structure, material and flywheel winding of super highspeed flywheels. Therefore, in this paper, electric flywheel energy and power density parameters are designed based on CPE (Continuous Power Energy) function and vehicle dynamics. Then, according to the design index requirements, the structure, size and material of the electric flywheel rotor are designed. Furthermore, the numerical analysis model of stress and displacement of multi-ring interference fit flywheel rotor under plane stress state is established. On this basis, the influence laws of flywheel rotor wheel flange numbers and interlaminar interference on stress distribution of flywheel rotor are analyzed, and the assembly form of wheel flange is determined. Finally, the stress check of the flywheel rotor is completed. The results show that the super highspeed flywheel rotor designed in this paper meets vehicle dynamics requirements in terms of energy storage and power. In terms of strength, it meets the design requirements of static assembly stress and dynamic stress at maximum speed. Full article

The energy consumption of passenger vehicles is affected by the physical properties of the environment. The ambient temperature in particular has a significant impact on the operating energy consumption. To quantify the impact of a changed climate on vehicles with different drivetrain systems, we set up a model that calculates the change in energy demand with respect to multiple global warming levels. In particular, the effect of rising temperatures on the energy consumption of battery electric vehicles and vehicles with internal combustion engines was investigated. Our results indicate that climate change will likely lead to a rise in energy consumption of vehicles with an internal combustion engine. This is mostly due to the increase in cabin climatization needs caused by the higher ambient temperatures. At a global warming level (GWL) of 4.0 °C, the calculated annual energy consumption on average is 2.1% higher than without taking the climate-change-related changes in temperature into account. Battery electric vehicles, on the other hand, are expected to have a lower overall energy consumption (up to −2.4% at 4 °C GWL) in cold and moderate climate zones. They benefit from the lower heating needs during winter caused by global warming. Full article

E-mobility is a key element in the future energy systems. The capabilities of EVs are many and vary since they can provide valuable system flexibility services, including management of congestion in transmission grids. According to the literature, leaving the charging process uncontrolled could hinder some of the present challenges in the power system. The development of a suitable charging management system is required to address different stakeholders’ needs in the electro-mobility value chain. This paper focuses on the design of such a system, the TwinEV module, that offers high-value services to electric vehicles (EV) users. This module is based on a Smart Charging Tool (SCT), aiming to deliver a more user-central and cooperative approach to the EV charging processes. The methodology of the SCT tool, as well as the supportive optimization algorithm, are explained thoroughly. The architecture and the web applications of TwinEV module are analyzed. Finally, the deployment and testing results are presented. Full article

With the enhancement of environmental awareness, China has put forward new carbon peak and carbon neutrality targets. Electric vehicles can effectively reduce carbon emissions in the use stage, and some retired power batteries can also be used in echelon, so as to replace the production and use of new batteries. How to calculate the reduction of carbon emission by the echelon utilization of retired power batteries in energy storage power stations is a problem worthy of attention. This research proposes a specific analysis process, to analyze how to select the appropriate battery type and capacity margin. Taking the BYD power battery as an example, in line with the different battery system structures of new batteries and retired batteries used in energy storage power stations, emissions at various stages in different life cycles were calculated; following this in carbon emission, reduction, by the echelon utilization of the retired power battery, was obtained. Finally, the overall carbon emissions that might be reduced by echelon utilization in the future were calculated according to the BYD’s battery loading volume and China’s total power battery loading volume in 2021. This research provides a quantitative analysis idea for the carbon emission reduction of power battery echelon utilization. Using this method could improve the process of echelon utilization, optimize the supply chain of power batteries, drive the development of the new-energy vehicle industry, and explore new business models, so as to achieve the environmental protection goal of carbon neutrality. Full article

The energy transition, a process in which fossil fuels are being replaced by cleaner sources of energy, comes with many challenges. The intrinsic uncertainty associated with renewable energy sources has led to a search for complementary technologies to tackle those issues. In recent years, the use of electric vehicles (EVs) has been studied as an alternative for storage, leading to a much more complex market structure. Small participants are now willing to provide energy, helping to keep the desired balance of supply and demand. In this paper, we analyse the electricity spot market, providing a model where EVs decide to participate depending on the underlying conditions. We study pricing rules adapted from versions currently in use in electricity markets, and focus on two of them for our experimental settings: integer programming (IP) and extended locational marginal (ELM) pricing. We particularly pay attention to the properties those prices might satisfy, and numerically test them under some scenarios representing different levels of participation of EVs and an active demand side. Our results suggest that IP pricing generally derives larger individual uplift payments and further produces public prices that are not well aligned with the final payments of market participants, leading to distortions in the market. Full article

Freight transport accounts for about half of all distances travelled in Europe. Therefore, freight transport is one of the decisive factors for reducing greenhouse gases and air pollutants. For this reason, the electrification of road freight transport is being promoted as part of the project “BEV Goes eHighway—[BEE]”. The data basis for the modelling used in this project is an electric drive axle for a heavy commercial vehicle, which was developed in the “Concept-ELV²” project. Based on the results of the previous project, the methodological tools that were developed are presented in this paper. These allow a wide range of possible powertrain topologies to be considered at the concept stage of development based on an estimation of future system characteristics. For this purpose, the components are automatically designed taking into account the mutual influence of the requirements and are evaluated in the context of the holistic system. This publication focuses on the efficiency and thermal evaluation of the transmission stages of the addressed electric drive units and validates the developed models using a pototypically designed electric commercial vehicle axle. Full article

This article focuses on the trajectory tracking problem in the actuation control section of autonomous vehicles. Based on a two-degrees-of-freedom dynamics model, this paper combines adaptive preview control with a second-order sliding mode control method to develop a new control method. By designing an objective function based on lateral deviations, road boundaries, and the corresponding characteristics of the overall vehicle motion, the method adaptively adjusts the preview time to obtain the ideal yaw rate and then uses a second-order sliding mode control algorithm named Super-Twisting to calculate the steering wheel angle. Combining the low-pass filter with this controller can effectively suppress the chattering caused by the switching of the sliding mode plane while proposing a concept of smoothing based on gradient derivative, the smoothness after filtering is one-seventeenth of that before filtering, whereas the phase plane is used to prove its effectiveness and stability, it can be seen from the phase diagrams that all the state points are in the stable region. A joint simulation model of Matlab/Simulink and Carsim was built to verify the control effectiveness of the controller under the double-shift road, and the simulation results show that the designed controller has good control effect and high tracking accuracy. Meanwhile, the simulation model is also used for other simulations, firstly, simulation comparison tests were carried out with the Model Predictive Control algorithm at speeds of 36 and 54 km/h, compared to the MPC controller, the tacking accuracy of the ST controller has improved to 64.42% and 51.02% at 36 and 54 km/h; secondly, taking simulation of the designed controller against a conventional sliding mode controller based on isokinetic law of convergence, compared to the CSMC controller, the tracking accuracy of the ST controller has improved 41.78% at 54 km/h, and the smoothness of the ST controller is one-nineteenth of that of the CSMC controller; thirdly, carrying out simulations on parameter uncertainties, and replacing parameter uncertainty with Gaussian white noise, the maximum tracking error at 36 and 54 km/h did not exceed 0.3 m, and tracking remains good. Small fluctuations in the steering wheel angle do not affect the normal actuation of the actuator. Full article

An important area of research in electric vehicle wireless power transfer systems is the detection of the secondary pad, which is vital evidence to determine whether the vehicle is in the effective charging area. However, the detection based on sensors mostly will reconstruct the vehicle structure and has a limit on versatility in all kinds of vehicles and the applicability of magnetic couplers and the influence on the primary pad. Therefore, an auxiliary pad structure and corresponding positioning method for offset estimation utilizing the existing inverter and secondary pad in the vehicle system are proposed. Firstly, to satisfy the needs of different positioning heights and avoid the effect on the primary pad, a triple-U positioning auxiliary pad is designed to assist positioning. Secondly, the direction-guided trajectory and detection algorithm are proposed to modify the vehicle location in real-time after analyzing the corresponding equivalent mutual inductance feature trajectory, according to the magnetic field characteristics of various typical magnetic couplers intervened by the proposed triple-U auxiliary pad. Finally, a prototype system is built to validate the applicability and feasibility of the triple-U auxiliary pad, where the positioning accuracy is within 10 mm, and the maximum recognizable recognition range can reach 300 mm × 300 mm, and the direction-guided trajectory is accurate, which can satisfy the actual positioning requirements of electric vehicles. Full article

It is expected that more vehicles will be electrified in the coming years. This will require reliable access to charging infrastructure in society, and the charging will include data exchange between different actors. The aim of this review article is to provide an overview of recent scientific literature on different charging strategies, including for example battery swapping, conductive- and inductive charging, and what data that may be needed for charging of different types of electric vehicles. The methodology of the paper includes investigating recent scientific literature and reports in the field, with articles from 2019 to 2022. The contribution of this paper is to provide a broad overview of different charging strategies for different types of electric vehicles, that could be useful today or in the coming years. The literature review shows that data utilized for charging or discharging includes for example information on the battery, temperature, electricity cost, and location. It is concluded that the preferred charging strategy for an electric vehicle may depend on the type of electric vehicle and when, where, and how the vehicle is used. Full article

In this paper, an analogous study of the velocity and temperature profiles inside microchannel cooling plates (with hydraulic diameter of 6 mm), placed on a large pouch-type LiFePO₄ battery, is presented using both the laboratory and simulation techniques. For this, we used reverse engineering (RE), computed tomography (CT) scanning, Detroit Engineering Products (DEP) MeshWorks 8.0 for surface meshing of the cold plate, and STAR CCM+ for steady-state simulation. The numerical study was conducted for 20 A (1C) and 40 A (2C) and different operating temperatures. For experimental work, three heat flux sensors were used and were intentionally pasted at distributed locations, out of which one was situated near the negative tab (anode) and the other was near the positive tab (cathode), because the heat production is high near electrodes and the one near the mid body. Moreover, the realizable k-ε turbulence model in STAR CCM+ is used for simulation of the stream in a microchannel cooling plate, and the computational fluid dynamics (CFD) simulations under constant current (CC) discharge load cases are studied. Later, the validation is conducted with the lab data to ensure sufficient cooling occurs for the required range of temperature. The outcome of this research work shows that as C-rates and ambient temperature increase, the temperature contours of the cooling plates also increase. Full article

This paper investigates and compares the torque-generating capabilities and electromagnetic performance of advanced non-overlapping winding induction machines (AIM), conventional induction machines (CIM), and interior-permanent magnet (IPM) machines for electric vehicle (EV) applications. All investigated machines are designed based on the specifications of the Toyota Prius 2010 IPM machine. The steady-state and flux-weakening performance characteristics are calculated by employing the 2D finite element method and MatLab, and the obtained results are quantitatively compared. Furthermore, the torque-generating capabilities of three machines are investigated for different electric loadings, and the machine having the highest torque-generating capability is determined as AIM. Moreover, the major parameters affecting the torque-generating capability, such as magnetic saturation and magnet demagnetization, are examined in depth. Full article

The transport sector has to be widely decarbonized by 2050 to reach the targets of the Paris Agreement. This can be performed with different drive trains and energy carriers. This paper explored four pathways to a carbon-free transport sector in Germany in 2050 with foci on electricity, hydrogen, synthetic methane, or liquid synthetic fuels. We used a transport demand model for future vehicle use and a simulation model for the determination of alternative fuel vehicle market shares. We found a large share of electric vehicles in all scenarios, even in the scenarios with a focus on other fuels. In all scenarios, the final energy consumption decreased significantly, most strongly when the focus was on electricity and almost one-third lower in primary energy demand compared with the other scenarios. A further decrease of energy demand is possible with an even faster adoption of electric vehicles, yet fuel cost then has to be even higher or electricity prices lower. Full article

There is an exponential increase in electric vehicles on the road that need a follow up in terms of warranty. The proposed state of warranty (SOW) is a metastate that qualitatively describes the warranty fulfillment level of an electric vehicle. All the relevant warranty information is synthesized in a single merit while maintaining the level of detail through the qualitative substates. The developed SOW is calculated with a rule-based logic of an expert system that evaluates the quantitative value of three substates: the remaining warranty, the remaining health and the remaining useful warranty. The SOW provides a synthesized and user-friendly description of the warranty fulfillment state while providing quantitative detailed information of the most relevant features of each of the different maintenance methodologies. Full article

The transportation environment of the open-pit mine is complex, the steering actuator of the mine vehicle has a large delay and poor response accuracy, and there are a lot of bumpy roads, large undulating ramps, and narrow-area curves in the mining area. These road sections seriously reduce the tracking accuracy of the mine vehicle path. Tracking control presents great challenges. Therefore, this study first conducts a simulation comparison study on commonly used path tracking methods such as pure pursuit control, Stanley control, and model predictive control (MPC), and then designs a path tracking control strategy for automatic driving of open-pit mine transportation vehicles based on the MPC algorithm. Finally, the proposed control strategy was verified through actual mining vehicle tests. The results showed that the maximum lateral deviation obtained by the MPC-based path tracking control strategy was reduced from 0.55 m to 0.08 m under the C-shaped reference path compared with the traditional method. Under the S-shaped reference path, the lateral deviation is reduced from 0.4 m to 0.16 m. Full article

Electric vehicles use wireless energy transmission to obtain energy, which can effectively avoid the shortcomings of traditional methods. As the carrier of radio energy transmission and reception, the high temperature of the coil triggers the degradation of wireless transmission performance and the aging of the coil, which may cause fire and other safety problems in serious cases. This paper studied the temperature distribution of the magnetically coupled coil model for electric vehicles. Based on the study of the basic law of heat transfer, the coil model was established using ANSYS software, and the boundary conditions and relevant parameters were set. After many simulation experiments and comparisons, it was finally determined that the transmitting coil and the receiving coil were the same sizes, the inner diameter of the coil was 100 mm, the outer diameter of the coil was 181 mm, and the coupling distance between the transmitting coil and the receiving coil was set to 60 mm. Coil models were simulated and analyzed using different materials. The simulation results show that after 30 min of system operation, the material chosen from the temperature range may have been gold, silver, copper, or aluminum, but from the comprehensive consideration of cost and performance, the material of the coil in the model was finally set to copper. Copper was the best material; its temperature maximum was 74.952 °C and lower than the safety value of 80 °C. It is hoped that this study will provide a reference for wireless charging coil design. Full article

Range anxiety is a significant contributor to consumer reticence when purchasing electric vehicles (EVs). To alleviate this concern, new commercial EVs readily achieve over 200 miles of range, as found by the United States Environmental Protection Agency (EPA). However, this range, measured under idealized conditions, is often not encountered in real-world conditions. As a result, this effort describes the simplest model that incorporates all key factors that affect the range of an EV. Calibration of the model to EPA tests found an average deviation of 0.45 and 0.57 miles for highway and city ranges, respectively, among seven commercial EVs. Subsequent predictions found significant losses based on the impact of road grade, wind, and vehicle speed over a Kansas interstate highway. For cabin conditioning, up to 57.8% and 37.5% losses in range were found when simulating vehicles at 20 °F and 95 °F, respectively. Simulated aging of the vehicle battery pack showed range losses up to 53.1% at 100,000 miles. Model extensions to rain and snow illustrated corresponding losses based on the level of precipitation on the road. All model outcomes were translated into an Excel spreadsheet that can be used to predict the range of a generic EV over Kansas-centric roads. Full article

The rise in electric vehicle uptake has reshaped the German mobility landscape at unprecedented speed and scale. While public charging is pivotal to growing the electric vehicle market, municipalities can play a crucial role in accelerating the energy transition in transport. This research aims to assist municipalities in planning their strategic rollouts of public charging infrastructure in size and location. In the first step, charging demand is estimated based on four development scenarios in 2030 of EV adoption and public charging. In a second step, a geospatial analysis was performed on the study area. Supply and demand criteria were considered to reflect the attractiveness of each location on a grid map. While the supply criteria represent constraints related to infrastructure availability, the demand criteria are categorized into three dimensions: residential, commercial, and leisure. The prioritization of demand criteria was derived from the municipality’s input using the analytical hierarchy process method to reflect its strategy. After obtaining the suitability index map, a cluster analysis was performed using a k-means clustering algorithm to ensure adequate geographical coverage of the charging network. Finally, the proposed charging stations in each scenario were allocated to the top-scoring locations, establishing a municipal public charging network. Full article