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CHARGE-MAP: An integrated framework to study the multicriteria EV charging infrastructure expansion problem

The widespread adoption of electric vehicles (EVs) in recent years has necessitated the development of effective charging infrastructures. However, charging infrastructure expansion is a multifaceted problem that requires careful consideration of the existing infrastructure, spatiotemporal distribution of charging demands, power-grid capacity, and budget constraints. Here, to approach this complex problem, we present CHARGE-MAP, a data-driven simulation-optimization framework, focused on ensuring meaningful charging experience for individual EV owners. CHARGE-MAP integrates three modules: an agent-based simulation module that estimates spatiotemporal distribution of charging demands by modeling EV adopter mobility and charging behavior; an optimization module that determines optimal new charging station/charger locations and capacities, while minimizing expected detour distances and wait-times with a limited number of new stations; and a power module that determines how to connect the stations to the power grid while maintaining its stability. Using the state of Virginia (consisting of 95 counties and 38 independent cities) as a case study, our results show that CHARGE-MAP can meet the demand of ~198,600 predicted EVs with 1,305 new public charging stations and 2,164 new chargers. It reduces average detour distances for charging by 66% and wait-times at stations by 72% compared to the existing infrastructure. Furthermore, transformer capacity requirement analysis reveals that only 1.8% of residential transformers require upgrades, while over 80% of commercial charging locations can be supported with modest transformer infrastructure (25 to 50 kVA). This indicates that targeted investments can facilitate cost-effective EV integration. Consequently, CHARGE-MAP provides policymakers and urban planners with crucial data-driven insights for effective EV charging infrastructure expansion. Sign up for PNAS alerts.

charging infrastructure

Analyzing Residential Charging Demand for Light-Duty Electric Vehicles in Colorado

The past decade has witnessed a remarkable surge in adoption of electric vehicles (EVs). The momentum is expected to continue with strong support from governments and industry. Rapid EV adoption will add significant electricity demand, making it critical to plan for and manage EV charging to avoid causing additional stress and non-negligible risks to the already-aging power grid. To help power grid operators understand the impacts of residential EV charging and identify risk factors, this study presents a data-driven charging demand analysis for light-duty vehicles. This study considers two real-world grid service regions in Colorado and merges multiple data sources and state-of-the-art tools that characterize EV adoption projections, vehicle travel patterns, seasonal variations, residential charging accessibility, ambient temperature impact, EV charging behaviors, grid utility customers, vehicle registration, and household-level EV charging demand distribution. We characterize potential residential charging demand in 2030 for two regions within the state of Colorado: Boulder and Aurora regions. We project that EVs will be 26% of the light-duty vehicle population in Boulder and 16% in Aurora areas. Charging demand is characterized for ten power grid feeders (five for each study region). Across the ten feeders, peak total EV charging powers during wintertime range from less than 1 MW to more than 4 MW.

ADVANCED PROPULSION SYSTEMS

Characteristics of Extreme Auroral Charging Events

The highest level spacecraft charging observed in low Earth orbit (LEO) occurs when spacecraft are exposed to energetic auroral electrons. Since auroral charging has been identified as a mechanism responsible for on-orbit anomalies and even possible satellite failures it is important to consider extreme auroral charging events as design and test environments for spacecraft to be used in high inclination LEO orbits. This paper will report on studies of extreme auroral charging events using data from the SSJ/4 and SSJ/5 precipitating electron and ion sensors on the Defense Meteorology Satellite Program (DMSP) satellites. Early studies of DMSP charging to negative potentials ≥100 V focused on statistics of the electron environment responsible for charging. Later statistical studies of auroral charging have generally focused on solar cycle dependence of charging behavior and magnitude of the maximum potential and duration of the charging events. We extend these studies to focus on more detailed investigations of extreme charging event characteristics that are required to evaluate potential threats to spacecraft systems. A collection of example auroral charging events is assembled from the DMSP data set using the criteria that "extreme auroral charging" is defined as periods with spacecraft negative potentials ≥400 V. Specific characteristics to be treated include (but are not limited to) maximum and mean potentials, time history of spacecraft potentials through the events, total charging duration and the time potentials exceed voltage thresholds, frame charging/discharging rates, and information on geographic and geomagnetic latitudes at which the events are observed. Finally, we will comment on the implications of these studies for potential auroral charging risks to the International Space Station.

Minow, Joseph I.

Discharges on a negatively biased solar array in a charged particle environment

The charging behavior of a negatively biased solar cell array when subjected to a charged particle environment is studied in the ion density range from 200 to 12 000 ions/sq cm with the applied bias range of -500 to -1400 V. The profile of the surface potentials across the array is related to the presence of discharges. At the low end of the ion density range the solar cell cover slides charge to from 0 to +5 volts independent of the applied voltage. No discharges are seen at bias voltages as large as -1400 V. At the higher ion densities the cover slide potential begins to fluctuate, and becomes significantly negative. Under these conditions discharges can occur. The threshold bias voltage for discharges decreases with increasing ion density. A condition for discharges emerging from the experimental observations is that the average coverslide potential must be more negative than -4 V. The observations presented suggest that the plasma potential near the array becomes negative before a discharge occurs. This suggests that discharges are driven by an instability in the plasma.

Snyder, D. B.

Discharges on a negatively biased solar cell array in a charged-particle environment

The charging behavior of a negatively biased solar cell array when subjected to a charged particle environment is studied in the ion density range from 200 to 12,000 ions/sq cm with the applied bias range of -500 to -1400 V. The profile of the surface potentials across the array is related to the presence of discharges. At the low end of the ion density range the solar cell cover slides charge to from 0 to +5 volts independent of the applied voltage. No discharges are seen at bias voltages as large as -1400 V. At the higher ion densities the cover slide potential begins to fluctuate, and becomes significantly negative. Under these conditions discharges can occur. The threshold bias voltage for discharges decreases with increasing ion density. A condition for discharges emerging from the experimental observations is that the average coverslide potential must be more negative than -4 V. The observations presented suggest that the plasma potential near the array becomes negative before a discharge occurs. This suggests that discharges are driven by an instability in the plasma.

Snyder, D. B.

Scalability and Effectiveness of Smart Charge Management

The rise in electric vehicle (EV) adoption presents growing challenges for power grids, particularly from simultaneous residential charging, which can cause voltage fluctuations and increase feeder peak loads. Baltimore Gas and Electric (BGE), with support from the U.S. Department of Energy, initiated a pilot program to evaluate managed residential EV charging through Smart Charge Management (SCM). This study analyzes real-world charging behavior data from the pilot and feeder-level base loads from BGE to simulate residential charging scenarios through 2035 across the Washington, DC–Baltimore region. Grid impacts under unmanaged charging are compared to three SCM strategies: TOU-immediate, TOU-distributed, and Load Balancing. Results show that the magnitude of peak reduction is highly feeder-dependent. Some feeders achieve reductions of more than 40% at high enrollment levels, while others show improvements closer to 10–15%. This heterogeneity reflects differences in baseline feeder load shapes, EV penetration, and plug-in behavior across customers. Results also highlight trade-offs between shifting load away from peak periods and minimizing secondary demand peaks, offering practical insights for future utility program design.

Electric vehicle

Unsupervised Detection of SOC Spoofing in OCPP 2.0.1 EV Charging Communication Protocol Using One-Class SVM

The electric vehicles (EVs) market keeps growing globally; thus, it is critical to secure the EV charging communication protocols in order to guarantee reliable and fair charging operations among the customers. The Open Charge Point Protocol (OCPP) 2.0.1 supports the communication between the Electric Vehicle Supply Equipment (EVSE) and Charging Station Management Systems (CSMSs); therefore, it becomes vulnerable to several types of attacks, which aim to jeopardize smart charging, billing, and energy management. Specifically, OCPP 2.0.1 allows the self-reporting of the State of Charge (SOC) values, which makes it vulnerable to spoofing-based cyberattacks, which target manipulating the scheduling priorities, distorting the load forecasts, and extending the charging sessions in an unfair manner. In this paper, we try to address this type of attack by providing a comprehensive analysis of the SOC spoofing attacks and introducing a novel unsupervised detection framework based on the One-Class Support Vector Machine (OCSVM) algorithm. Specifically, two types of attack scenarios are analyzed (i.e., priority manipulation and session extension) by deriving engineered features that capture the nonlinear relationships under normal charging behavior. Detailed simulation-based results are derived by utilizing the DESL-EPFL Level 3 EV charging dataset. Our results demonstrate high F1-score and recall in identifying spoofed SOC values and that the proposed OCSVM model demonstrates superior performance compared to alternative clustering and deep-learning based detectors.

EV charging

Spacecraft Charging Sensitivity to Material Properties

Evaluating spacecraft charging behavior of a vehicle in the space environment requires knowledge of the material properties relevant to the charging process. Implementing surface and internal charging models requires a user to specify a number of material electrical properties including electrical resistivity parameters (dark and radiation induced), dielectric constant, secondary electron yields, photoemission yields, and breakdown strength in order to correctly evaluate the electric discharge threat posed by the increasing electric fields generated by the accumulating charge density. In addition, bulk material mass density and/or chemical composition must be known in order to analyze radiation shielding properties when evaluating internal charging. We will first describe the physics of spacecraft charging and show how uncertainties in material properties propagate through spacecraft charging algorithms to impact the results obtained from charging models. We then provide examples using spacecraft charging codes to demonstrate their sensitivity to material properties. The goal of this presentation is to emphasize the importance in having good information on relevant material properties in order to best characterize on orbit charging threats.

Minow, Joseph I.

EV Profile Capture

NextGen Profiles' EV profile capture efforts aimed to explore the variance in performance and evaluate how different operational conditions influence production EV charging behavior. Data were collected at a frequency of 10 Hz from both the EV and EVSE during each charge session. These charge session parameters were then entered into a time-series database for further analysis. The data were gathered under different operational conditions to examine the effects of various factors such as battery state of charge, battery temperature, vehicle condition, smart charge management, and EVSE limitations. The EV profile capture dataset includes extensive high-power charging data from 16 different EVs—comprising light-, medium-, and heavy-duty vehicles—along with EVSE from various suppliers. To protect confidentiality, the EV and EVSE metadata are anonymized, and the publicly released datasets are aggregated to 0.1-Hz frequency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Effects of secondary electron emission on charging

Laboratory charging studies using two electron sources with different energies show that the charging behaviors of typical spacecraft thermal control dielectric surface are extremely sensitive to the shape of their secondary emission curves. The results also suggest that the electron spectrum in a natural charging environment can be separated into three distinct regions (noninteracting, discharging, and charging) depending on the kinetic energy of the incident electron relative to the charged surface, and on the secondary emission characteristics of the material. To a first order approximation, the relative number of electrons in these different regions determines the potential of the charged surface. Detailed measurements of the secondary electron emission characteristics of Kapton, the effects of bulk conductivity and secondary emission on surface charging of these materials is reported.

Leung, M. S.

An Agent-Based Modeling Approach for Spatiotemporal Optimization of Electric Vehicle Fast-Charging Station Demand

With increasing electric vehicle (EV) adoption, managing public fast-charging demand effectively is crucial to avoid grid strain. This study investigates the potential of using dynamic pricing schemes to address this challenge. Presented in this study is a scalable agent-based simulation framework, which is applied to a case study in Richmond, Virginia, that assumes a 50% EV adoption rate in 2040. Two pricing schemes are compared: (1) a dynamic-pricing scheme based on station utilization and (2) a dynamic-pricing scheme based on peak power at the station. These schemes are compared to two baseline scenarios: (1) unscheduled first-come, first-served and (2) scheduled with constant price. The study’s results suggest that dynamic pricing has the potential to influence EV charging behavior, inducing both spatial and temporal shifts, but does so at the cost of inducing inconvenience to EV drivers. The results suggest the peak-power dynamic pricing scheme has the potential to mitigate peak demand pressures on the grid with minimal inconvenience, offering a promising approach for sustainable EV charging infrastructure expansion.

33 - ADVANCED PROPULSION SYSTEMS

Data Quality Assessment of Optiwatt Vehicle Telematics Data

In October 2024, the Idaho National Laboratory (INL) received data from Optiwatt (Compass Global, Inc.) describing the driving and charging behavior of electric vehicle (EV) drivers. The data shared had been collected from approximately 10,000 vehicles and included vehicle specifications, driving information like odometer readings at the beginning and end of origin-destination pairs (i.e., trips with identification of home for trip start and end for Tesla vehicles), and charging information such as charging energy consumed per charge session and if the charge occurred at home. The vehicle data were provided from 9 EV makes and 18 EV models, with production years ranging from 2012–2024, but more than 9,500 of the vehicles were Tesla EVs. The data includes more than six million trips and more than three million charging events that occurred between June 2023 to Aug 2024 and collected from California and the Eastern United States. The purpose of this report is to review the quality of the data received from Optiwatt and the feedback INL received from Optiwatt after data concerns were shared with them.

33 - ADVANCED PROPULSION SYSTEMS

Results From Mars Show Electrostatic Charging of the Mars Pathfinder Sojourner Rover

Indirect evidence (dust accumulation) has been obtained indicating that the Mars Pathfinder rover, Sojourner, experienced electrostatic charging on Mars. Lander camera images of the Sojourner rover provide distinctive evidence of dust accumulation on rover wheels during traverses, turns, and crabbing maneuvers. The sol 22 (22nd Martian "day" after Pathfinder landed) end-of-day image clearly shows fine red dust concentrated around the wheel edges with additional accumulation in the wheel hubs. A sol 41 image of the rover near the rock "Wedge" (see the next image) shows a more uniform coating of dust on the wheel drive surfaces with accumulation in the hubs similar to that in the previous image. In the sol 41 image, note particularly the loss of black-white contrast on the Wheel Abrasion Experiment strips (center wheel). This loss of contrast was also seen when dust accumulated on test wheels in the laboratory. We believe that this accumulation occurred because the Martian surface dust consists of clay-sized particles, similar to those detected by Viking, which have become electrically charged. By adhering to the wheels, the charged dust carries a net nonzero charge to the rover, raising its electrical potential relative to its surroundings. Similar charging behavior was routinely observed in an experimental facility at the NASA Lewis Research Center, where a Sojourner wheel was driven in a simulated Martian surface environment. There, as the wheel moved and accumulated dust (see the following image), electrical potentials in excess of 100 V (relative to the chamber ground) were detected by a capacitively coupled electrostatic probe located 4 mm from the wheel surface. The measured wheel capacitance was approximately 80 picofarads (pF), and the calculated charge, 8 x 10(exp -9) coulombs (C). Voltage differences of 100 V and greater are believed sufficient to produce Paschen electrical discharge in the Martian atmosphere. With an accumulated net charge of 8 x 10(exp -9) C, and average arc time of 1 msec, arcs can also occur with estimated arc currents approaching 10 milliamperes (mA). Discharges of this magnitude could interfere with the operation of sensitive electrical or electronic elements and logic circuits. Sojourner rover wheel tested in laboratory before launch to Mars. Before launch, we believed that the dust would become triboelectrically charged as it was moved about and compacted by the rover wheels. In all cases observed in the laboratory, the test wheel charged positively, and the wheel tracks charged negatively. Dust samples removed from the laboratory wheel averaged a few ones to tens of micrometers in size (clay size). Coarser grains were left behind in the wheel track. On Mars, grain size estimates of 2 to 10 mm were derived for the Martian surface materials from the Viking Gas Exchange Experiment. These size estimates approximately match the laboratory samples. Our tentative conclusion for the Sojourner observations is that fine clay-sized particles acquired an electrostatic charge during rover traverses and adhered to the rover wheels, carrying electrical charge to the rover. Since the Sojourner rover carried no instruments to measure this mission's onboard electrical charge, confirmatory measurements from future rover missions on Mars are desirable so that the physical and electrical properties of the Martian surface dust can be characterized. Sojourner was protected by discharge points, and Faraday cages were placed around sensitive electronics. But larger systems than Sojourner are being contemplated for missions to the Martian surface in the foreseeable future. The design of such systems will require a detailed knowledge of how they will interact with their environment. Validated environmental interaction models and guidelines for the Martian surface must be developed so that design engineers can test new ideas prior to cutting hardware. These models and guidelines cannot be validated without actual flighata. Electrical charging of vehicles and, one day, astronauts moving across the Martian surface may have moderate to severe consequences if large potential differences develop. The observations from Sojourner point to just such a possibility. It is desirable to quantify these results. The various lander/rover missions being planned for the upcoming decade provide the means for doing so. They should, therefore, carry instruments that will not only measure vehicle charging but characterize all the natural and induced electrical phenomena occurring in the environment and assess their impact on future missions.

Kolecki, Joseph C.

Electrostatic Charging of the Lunar Surface

Lunar regolith dust particles accumulate charge and interact electrostatically with rover wheels, astronaut boots, and equipment. We have developed instrumentation for in situ measurements of the electrostatic charge developed by the interactions of lunar regolith dust with the space-rated materials on these devices. This instrument is also capable of measuring the distribution of electric fields on or near the lunar surface and the ion currents present near the lunar surface. We also report on our efforts to characterize the charging behavior of lunar dust in low gravity environments. This behavior is nonintuitive due to complex interactions between individual dust grains. We are developing an experiment to study this interaction in a microgravity vacuum environment. Better understanding of this interaction will allow for improved dust mitigation on the lunar surface.

electrostatics

Electrostatic charging of the lunar regolith

Lunar regolith dust particles accumulate charge and interact electrostatically with rover wheels, astronaut boots, and equipment. We have developed instrumentation for in situ measurements of the electrostatic charge developed by the interactions of lunar regolith dust with the space-rated materials on these devices. This instrument is also capable of measuring the distribution of electric fields on or near the lunar surface and the ion currents present near the lunar surface. We also report on our efforts to characterize the charging behavior of lunar dust in low gravity environments. This behavior is nonintuitive due to complex interactions between individual dust grains. We are developing an experiment to study this interaction in a microgravity vacuum environment. Better understanding of this interaction will allow for improved dust mitigation on the lunar surface.

electrostatics

Electrochemical dynamics of imidazolium ionic liquids at graphene electrodes for energy storage applications

Electric double layer capacitors (EDLCs) are prominent energy storage systems that constitute the foundation of more reliable and sustainable energy infrastructures. Modern EDLCs often incorporate ionic liquids (ILs) as a key component in their electrolytes, leveraging the high electrochemical stability of ILs to enhance device performance. The performance and functionality of these capacitors also hinge on the interfacial behavior of ILs at electrode surfaces, which remain insufficiently understood. Here, we performed synchrotron infrared nanospectroscopy (SINS) in combination with density functional theory (DFT) calculations to investigate the electric double layers (EDLs) of three imidazolium-based ILs in a custom-designed graphene liquid cell. This approach revealed new insights into the dynamics of IL EDLs and the underpinning factors originating from the IL structures. Variations in anion size and structure were found to tune the ILs’ ability to form EDLs with compact and closely-correlated ion arrangements, which are critical for enhancing their capacitive performance. These findings highlight the intricate interactions between ions governed by their structures and charge behaviors, which underscores the opportunities for targeted design of IL-based electrolytes to optimize EDLC functionality.

Electric double layers

Virtual refrigerant charge sensing algorithm for residential CO₂ heat pumps

Natural refrigerants are increasingly adopted in next-generation heat pump systems, among which CO₂ heat pumps have attracted significant attention. However, due to their high operating pressures, the leakage risk is higher, resulting in undercharge conditions and degraded heat pump performance. Thus, developing an accurate refrigerant charge level detection technique is necessary to guarantee safe and efficient operation. Although virtual refrigerant charge (VRC) level calculation algorithms for CO₂ heat pumps exist, they typically rely on empirically selected features without a systematic selection framework, leading to multicollinearity and potential overfitting, which limit their prediction accuracy and generalizability. To address these issues, this study proposes a VRC algorithm framework with a systematic feature selection method that identifies physically meaningful and statistically significant features, and is applied using a residential CO₂ heat pump as a case study. The method is extended from previous work on conventional refrigerants to account for charge behavior in CO₂ gas coolers. The selected features include gas cooler outlet density, evaporator pressure, and superheat temperature. The results demonstrate that the proposed feature selection method significantly improves prediction accuracy compared to existing VRC approaches. A relatively small training dataset (∼30 samples) is sufficient for feature identification and model development. The developed algorithm achieves less than 3% prediction error under both undercharge and overcharge conditions, representing reductions of 46.7% and 35.3% compared to two recent reference VRC algorithms for transcritical CO₂ heat pumps reported in the literature. The proposed algorithm and feature selection method enhance leakage detection capability, facilitate the deployment of CO₂ heat pump systems, and contribute to reduced energy waste and maintenance costs.

Guo, Fangzhou [Lawrence Berkeley National Laborato

Measuring pH Changes Inside a Bipolar Membrane Junction

Here, the local pH environment within bipolar membrane (BPM) junctions is complex and not well understood, yet it is important to control for advancing the performance of BPM-based electrochemical systems. We report a voltammetric strategy using an ultrathin Ni mesh pH probe to spatially resolve pH changes in the BPM junction during model BPM electrolyzer operation. Under reverse bias, we observe depletion of OH – at the anion-exchange layer (AEL) interface, with a degree diminishing with increasing distance from the AEL. These gradients correlate with current-dependent water dissociation (WD) and are modulated by the electric field and the surface charge state of the catalyst. By correlating spatial pH profiles with the surface-charging behavior of WD catalysts, we explore a mechanism of catalyst-mediated H + and OH – transfer facilitated by hydrogen-bonding networks. These findings highlight the role of local chemistry and electrostatics in BPM performance and offer new methods to probe and engineer catalytic junctions in electrochemical energy devices.

Hou, Shujin [University of California, Berkeley, C