Plug-in Electric Vehicle Battery Research Articles

Impact of Plug-In Electric Vehicle Battery Charging on a Distribution System Based on Real-Time Digital Simulator

Although the electric vehicles (EVs) have many economic and environmental advantages as compared to the conventional cars, the increased adoption of these vehicles will bring up new concerns for the power distribution grid in terms of introducing new peaks into the system or causing voltage quality problems. This study investigates the impact of the electric vehicles battery charging on the distribution system in terms of voltage unbalance at various locations, transformers overloading, and shifting the peak of the system. In this research, a 12.47 kV real distribution network has been modelled using real time digital simulator, using real data from a power distributor. The study presents four different scenarios of uncoordinated EVs integration for two different charging times (evening and night) and two different charging rates (level I and level II) at different penetration levels ranging from 10% to 100%. Voltage unbalance at different locations is determined and transformer overloading is analysed. The influence of EVs charging on the daily load curve is shown.

Delivering Energy from PEV batteries: V2G, V2B and V2H approaches

Plug-in electric vehicles (PEVs) sales have grown in the last years. Depending on the PEV model, each PEV can store approximately between 5-40 kWh of energy. This energy can be used not only for travel purposes but also for other appliances like providing energy for homes (V2H) or buildings (V2B) and even for supply ancillary services to distribution network operators, through vehicle to grid concept (V2G). This paper presents the different strategies that can be found in the literature about delivering energy from PEV batteries. Also, commercial solutions and pilot projects are presented.

Advanced control strategies to manage electric vehicle drivetrain battery health for Vehicle-to-X applications

The demand for local power resilience is promoting the installation of renewable-based microgrids. Plug-in electric vehicles (PEVs) are rapidly increasing and can play a critical role in microgrid service provision. The capability of bi-directional charging and discharging will transition PEVs from a simple means of transportation to multi-purpose value generating assets. They can balance the inherently fluctuating generation of renewable energy resources and shape customer’s electricity demand, while still providing the core service of transportation. Value stacking through those additional services allows PEV owners to draw from a number of revenue streams to offset investment costs. However, accelerated battery degradation is often cited as concern when using PEV batteries for purposes other than driving, which presents a major barrier for broad market adoption. This study seeks to assess the economics and trade-offs of bi-directional use of PEVs when utilized as fleet vehicles. In particular, the usage patterns and benefits for PEV fleet deployment at three U.S. military bases is presented. The results show operational cost benefits for bi-directional application of up to 60.8 % annual return on investment without managing battery health, and up to 106.0 % when actively managing battery health through advanced control strategies. The one year payback period far exceeds the expected installation lifespan of at least ten years. Given the results, utilizing PEV fleets for additional services at U.S. military bases can largely offset the additional cost of bi-directional charging hardware and software compared to standard uni-directional equipment.

Effective Utilization of Available PEV Battery Capacity for Mitigation of Solar PV Impact and Grid Support with Integrated V2G Functionality

Abstract: Utilizing battery storage devices in plug-in electric vehicles (PEVs) for grid support using vehicle-to-grid (V2G) concept is gaining popularity. With appropriate control strategies, the PEV batteries and associated power electronics can exploited for solar photovoltaic (PV) impact mitigation and grid support. However, as the PEV batteries have limited capacity and the capacity usage is also constrained by transportation requirements, an intelligent strategy is necessary for an effective utilization of the available capacity for V2G applications. In this paper, a strategy for an effective utilization of PEV battery capacity for solar PV impact mitigation and grid support is proposed. A controllable charging/ discharging pattern is developed to optimize the use of the limited PEV battery capacity to mitigate PV impacts, such as voltage rise during midday or to support the evening load peak. To ensure an effective utilization of the available PEV battery capacity when used for travel (which is the main usage of the PEVs) or when interventions in the charging operation is caused by passing clouds, a strategy for dynamic adjustments in PEV charging/discharging rates is proposed. The effectiveness of the proposed strategy is tested using a real distribution system in Australia based on practical PV and PEV data.

Automobile manufacturing in India by 2050 – War on EV

First-tier suppliers strive to cut costs while enhancing delivery lead times, dependability, and flexibility in the dynamic and competitive climate of the automotive sector. The development of electric cars has increased in several nations in order to lessen reliance on oil and environmental degradation. In order to prepare for their potential applications, this study discusses new technologies and vehicle production in India by 2050. A key component of India's carbon neutrality policy is the promotion of plug-in electric vehicles (PEVs). A net-zero emission goal by 2050, 500 GW of non-fossil fuel energy capacity by 2030, 50% of energy needs coming from renewable energy sources, a reduction of 1 billion tonnes of greenhouse gas emissions and a reduction of the economy's carbon intensity of less than 45% are five of India's new pledges. It is crucial to comprehend the growth of the automotive industry and its effects on prices, sales, industrial fuel efficiency, and the need for PEV battery materials.This research statistically analyses the dynamics of India's passenger car advertise from 2020 to 2050 under various technological development scenario by looking at vehicle technologies, costs, regulatory incentives, infrastructure, and driving behaviour. As a further addition, this study also addresses the technical difficulties and cutting-edge technologies for future advancements in the dependability, safety, and efficiency of EVs.

Representative Driving Cycles for Trinidad and Tobago with Slope Profiles for Electric Vehicles

The rise of plug-in battery electric vehicles presents an excellent opportunity for small island developing states such as those of the Caribbean. The vehicles offer improved energy efficiency, enhanced energy security, and reduced foreign exchange expenditure. Incentivizing the uptake of electric vehicles seems to be an obvious policy decision, but there could be unintended consequences. Real-world driving cycles are essential for validating electric-vehicle energy and economic benefits using simulation studies. In drive-cycle methodologies, the microtrip method is the preferred choice for countrywide representation and is ideal for fuel consumption estimations. This paper reports on the first such real-world driving cycle for the Caribbean, specifically Trinidad and Tobago, which is developed using a microtrip construction method with a novel approach to establishing a slope profile. Highway and suburban segments show some distinct characteristics, including relatively high average accelerations and decelerations in the highway and suburban cycles and low average speeds of 40.2 km/h (highway) and 21.74 km/h (suburban). The driving cycle is unique but reasonable when compared with others derived in emerging economies.

A User-Friendly Transactive Coordination Model for Residential Prosumers Considering Voltage Unbalance in Distribution Networks

Designing transactive energy (TE) markets in distribution systems has been a hot topic due to the increased presence of residential prosumers. In the literature, several residential market platforms have been proposed; however, they usually have two main drawbacks: 1) ignoring the effect of single-phase distributed energy resources on the voltage unbalance (VU) in active distribution networks to develop a transactive coordination model that will effectively mitigate the VU and 2) inability in providing a user-friendly strategy for home occupants to adjust the willingness to pay/accept of responsive assets according to their comfort and economic purposes. This article amends the shortcomings by proposing a network-constrained TE model to coordinate residential prosumers with the main goal of satisfying households’ preferences as well as mitigating distribution system problems. The case study is then carried out demonstrating that the proposed TE-concept-based coordination of residential prosumers is aligned with customers’ preferences (comfort and economic purposes) and concerns (plug-in electric vehicle battery life) and could effectively decrease the VU.

Transactive Energy Management of V2G-Capable Electric Vehicles in Residential Buildings: An MILP Approach

This paper proposes a new energy management model for residential buildings to handle the uncertainties of demand and on-site PV generation. For this purpose, the building energy management system (BEMS) organizes a transactive energy (TE) market among plug-in electric vehicles (PEVs) to determine their charge/discharge scheduling. According to the proposed TE framework, the PEV owners get reimbursed by the BEMS for the flexibility they offer. In this regard, the PEV owners submit their response curves for reimbursement upon arrival. Then, the BEMS solves an optimization problem to maximize its own profit and determine the real-time TE market-clearing price. Afterward, based on the clearing price, the real-time scheduling of PEV batteries and the reimbursements to the PEV owners for their responses are determined. Additionally, the original mixed-integer non-linear optimization problem is reformulated as a mixed-integer linear programming one using a set of linearization techniques. Finally, the proposed model is applied to a residential building with 50 PEV charging piles, and the simulation results show that the proposed model decreases the actual charging payment of PEV owners by 17.6% and 52.3%, and the total cost of BEMS by 5.1% and 10.8% compared to demand response concept-based and uncontrolled charging models, respectively.

Resource Availability and Implications for the Development of Plug-In Electric Vehicles

Plug-in electric vehicles (PEVs) have immense potential for reducing greenhouse gas emissions and dependence on fossil fuels, and for smart grid applications. Although a great deal of research is focused on technological limitations that affect PEV battery performance targets, a major and arguably equal concern is the constraint imposed by the finite availability of elements or resources used in the manufacture of PEV batteries. Availability of resources, such as lithium, for batteries is critical to the future of PEVs and is, therefore, a topic that needs attention. This study addresses the issues related to lithium availability and sustainability, particularly supply and demand related to PEVs and the impact on future PEV growth. In this paper, a detailed review of the research on lithium availability for PEV batteries is presented, key challenges are pinpointed and future impacts on PEV technology are outlined.

A Multiagent Federated Reinforcement Learning Approach for Plug-In Electric Vehicle Fleet Charging Coordination in a Residential Community

The increasing penetration of distributed renewable energy and electric vehicles (EV) in local microgrids/residential-community has brought a great challenge to balancing system stability and economic benefits. This paper proposes a decentralized framework based on an efficient federated deep reinforcement learning method for plug-in electric vehicle (PEV) fleet charging management in a residential community, which is equipped with a photovoltaic and battery energy storage system and connected to a local transformer. Firstly, the framework of PEV charging management is described as a virtual EV charging station coordinating charging tasks through sharing public information with distributed agents. Then, an individual preference model of PEV is developed considering heterogenous PEV charging anxiety, battery degradation, and collective penalty. Subsequently, we propose an attention-weighted federated soft-actor-critic method to efficiently seek the co-ordinational scheduling of the PEV fleet charging in a distributed way, where scalability and privacy protection can be ensured with attention-based information sharing. Finally, a real-world case study is conducted to validate the effectiveness and feasibility of the proposed approach.

Quantifying the emissions impact of repurposed electric vehicle battery packs in residential settings

The market share of plug-in electric vehicles (PEVs) is growing, thanks to improvements in battery efficiency, declining production costs, and sustained policy support. Concurrently, concerns are growing over the supply of decommissioned PEV batteries. This has attracted a growing interest among scientists to determine the utility of repurposing PEV batteries for energy storage. Previous work has optimized behind-the-meter (BTM) battery storage systems (BSSs) for self-sufficiency and energy arbitrage, but few have used the system to lessen a home's electricity-related carbon footprint. This study uses high-resolution 2018 electricity demand from energy-efficient homes in Austin, Texas and grid generation data to simulate the daily operations of a 6 kWh BTM-BSS to minimize daily CO2e emissions. Results suggest that such homes with rooftop solar can reduce electricity-related household CO2eemissions by 21%, on average (about 1 ton of CO2e annually), while homes without solar could reduce their CO2e emissions by just 2% (about 0.12 tons per year). Pairing a BSS with rooftop solar increases average annual carbon savings by greater energy retention and lessening demand from the grid during carbon-intense generation periods. To make BTM-BSSs cost-effective for Austin homeowners, the price of repurposed PEV batteries must fall to $5.71/kWh or per-ton carbon pricing must rise to $70.34 for homeowners to reach break-even over an estimated 10-year BSS lifespan.

Efficient Model for Accurate Assessment of Frequency Support by Large Populations of Plug-in Electric Vehicles

In recent years, plug-in electric vehicles (PEVs) have gained immense popularity and are on a trajectory of constant growth. As a result, power systems are confronted with new issues and challenges, threatening their safety and reliability. PEVs are currently treated as simple loads due to their low penetration. However, as their numbers are growing, PEVs could potentially be exploited as distributed energy storage devices providing ancillary services to the network. Batteries used in PEVs are developed to deliver instantaneously active power, making them an excellent solution for system frequency support. This paper proposes a detailed dynamic model that is able to simulate frequency support capability from a large number of PEVs, using an innovative aggregate battery model that takes into account the most significant constraints at PEV and aggregate battery levels. The cost optimization algorithm, which is the most time-consuming process of the problem, is executed only at the aggregate battery level, thereby reducing the computational requirements of the model without compromising the obtained accuracy. The proposed method is applied to the power system of Crete exploiting detailed statistical data of EV mobility. It is proven that PEVs can effectively support power system frequency fluctuations without any significant deviation from their optimal operation.

China's vehicle electrification impacts on sales, fuel use, and battery material demand through 2050: Optimizing consumer and industry decisions

SummaryThe promotion of plug-in electric vehicles (PEVs) is pivotal to China's carbon neutrality strategy. Therefore, it is important to understand the vehicle market evolution and its impacts in terms of costs, sales, industry fuel economy, and PEV's battery material demand. By examining vehicle technologies, cost, policy incentives, infrastructure, and driver behavior, this study quantitatively projects the dynamics of China's passenger vehicle market from 2020 to 2050 under multiple technology evolution scenarios. By 2050, battery electric vehicles could gain significant market share—as much as 30.4%–64.6%; and the industry's sales-weighted average fuel consumption could reach 1.81–3.11 L/100 km. Cumulative battery demand from PEVs could soar to over 700 GWh by 2050, whereas battery recycling alone could satisfy about 60% of the demand by 2050. The key metal supplies—lithium, cobalt, and nickel—for China's PEV market are projected, and nickel should be concerned more over the coming decades.

Quantifying energy flexibility of commuter plug-in electric vehicles within a residence–office coupling virtual microgrid. Part II: Case study setup for scenario and sensitivity analysis

Continuing with the model and methods proposed in Part I for the optimal coordination and flexibility evaluation of plug-in electric vehicles (PEVs), we further conducted a case study to assess the energy flexibility of commuter PEVs in a virtual microgrid in Beijing, consisting of distributed RES system, an office and residences. We first presented a parametric mobility model for generating individual driving profiles of commuter PEVs. The validation results indicated the feasibility of the model in capturing the mobility characteristics of commuter vehicles in Beijing. On that basis, the flexibility of PEVs for different charging schemes and renewable generation portfolios was evaluated. The results indicated that the expansion of charging locations primarily increases the flexibility potential for reducing power ramps, meanwhile, activating the Vehicle-to-Building (V2B) function mostly improve the potential for reducing energy and power capacity. By contrast, the charging locations expansion takes priority to the V2B capability. Finally, we further analyzed how the flexibility is influenced by PEV numbers, charging parameters and reserve levels. The results showed that the daily net load profile of the microgrid could be nearly flattened when the PEV battery storage quota per unit office area reaches 0.18 kWh/m2 in the studied case.

Enablers and disablers to plug-in electric vehicle adoption in India: Insights from a survey of experts

The Indian government is considering plug-in electric vehicle (PEV) deployment as one solution to address the issues of air pollution, energy security, and climate change. We investigate the potential for PEV adoption in India, the challenges in meeting the country’s goals and ways to overcome them. We utilize a survey of 51 experts in the Indian light-duty vehicle (LDV) ecosystem to address these questions. The majority of experts indicate that India will marginally miss its 30% PEV sales target by 2030. The main reasons cited for this are PEVs’ high upfront cost, a lack of policies promoting PEVs and a lack of charging infrastructure. Experts believe lack of domestic PEV battery and manufacturing supply chains will limit the supply of low-cost PEVs to the Indian market. The lack of land availability and high land rent prices in Indian cities is cited as the major barrier to the establishment of charging infrastructure. The experts view a PEV sales mandate and incentives, such as ‘feebates,’ as the most effective policy levers, while believing a ban on conventional vehicle sales by 2030 was unlikely. The findings hold significance for understanding the future of India’s LDV sector and the associated energy and environmental impacts, which have global implications.

Global perspective on CO2 emissions of electric vehicles

Plug-in electric vehicles (PEVs) are a promising option for greenhouse gas (GHG) mitigation in the transport sector - especially when the fast decrease in carbon emissions from electricity provision is considered. The rapid uptake of renewable electricity generation worldwide implies an unprecedented change that affects the carbon content of electricity for battery production as well as charging and thus the GHG mitigation potential of PEV. However, most studies assume fixed carbon content of the electricity in the environmental assessment of PEV and the fast change of the generation mix has not been studied on a global scale yet. Furthermore, the inclusion of up-stream emissions remains an open policy problem. Here, we apply a reduced life cycle assessment approach including the well-to-wheel emissions of PEV and taking into account future changes in the electricity mix. We compare future global energy scenarios and combine them with PEV diffusion scenarios. Our results show that the remaining carbon budget is best used with a very early PEV market diffusion; waiting for cleaner PEV battery production cannot compensate for the lost carbon budget in combustion vehicle usage.

A MILP model to relieve the occurrence of new demand peaks by improving the load factor in smart homes

Demand response (DR) programs based on pricing options allow residential customers to achieve a financial reduction in their energy bill due to changes in their consumption patterns, especially during peak periods. However, when a large number of consumers adopt this energy management program, the demand shifted to periods with low energy prices can generate new demand peaks. As a result, the quality of the power supply service may be compromised. To address this concern, this paper proposes a mixed-integer linear programming (MILP) model that aims to improve the load factor (LF) related to the demand profile of customers. To achieve this goal, an intelligent scheduling strategy for household appliances that considers flexibility in customer comfort, here called customer hourly preferences, is developed. Based on these preferences, the strategy seeks the efficient daily usage of smart appliances, mainly those with higher average power, to avoid its coincident consumption in periods with lower energy rates, thus mitigating the appearance of new peaks. In the proposed model, the operating expenses of both customers and the electricity company (ECO) are minimized. A set of technical and operational constraints such as the average power, number of times utilized, and average time of usage of home appliances, as well as the charging rate, average time for charging, and initial state-of-charge (SoC) of the plug-in electric vehicle (PEV) battery, are considered. Uncertainties related to the periods of the day when a given appliance (including PEV) is turned-on for consumption are modeled using a Monte Carlo Method (MCM). The MILP model is solved using a commercial solver CPLEX that makes use of classical optimization techniques to ensure the optimal solution to this problem. The performance of the MILP model was tested through two case studies. Case study 1 considers a group of consumers with the same income, while case study 2 triples the number of consumers in the previous case considering different incomes. The results show the importance of the proposed tool for analyzing and evaluating prospective scenarios that guarantee the efficient usage of electric energy with the lowest financial expense for both consumers and the ECO.

Electrification and renewable energy nexus in developing countries; an overarching analysis of hydrogen production and electric vehicles integrality in renewable energy penetration

As the world continues to fight against climate change, renewables have emerged as an imminent solution, however, a model that can help (developing) countries to effectively migrate to a renewable energy-based power sector is limited in literature. In this study, a comprehensive electricity generation analysis based on an hourly time-step is done in a bid to solve to electrification crisis in developing countries. This study aims to present the feasible pathways with which sustainable electrification can be achieved. This is done by considering the financial feasibility, environmental sustainability, and technical viability of different technological combinations. In comparison to existing literature, this study is novel as the integration of both renewable energy sources and a fossil fuel source is analyzed. With Nigeria being the study area, the integration of five renewable energy-based technologies namely; offshore wind power plant, onshore wind power plant, solar photovoltaic system, concentrated solar power plant, and hydropower plant as well as pumped hydro storage system is considered within the scope of this study. Based on the results of the analysis, out of the ninety-nine different combinatory scenarios modeled, the most viable solution with the use of renewables and natural gas is the combination of natural gas power plants, on-shore wind power plants, and solar photovoltaic systems. This requires a large capacity installation (32,500 MW of natural gas power plant, 12,000 MW of solar photovoltaic plant, and 7000 MW of on-shore wind power plant) as well as a total annual cost and an investment cost of $ 22B and $ 48.7B. Furthermore, solving the poised problem based on renewable energy technologies will only require the combination of on-shore wind power plants, hydropower plants, solar photovoltaic system, and pumped hydro storage system. The integration of plug-in battery electric vehicles and hydrogen production will help maximize the electricity produced from the renewable energy-based power systems. This will also reduce the overall carbon emission from the country at large. Beyond providing feasible scenarios and plans to tackle the existing electricity production, guidelines on steps (not to take) to tackle the electrification problem are embedded in this study.

Well-to-Wheels Analysis of Zero-Emission Plug-In Battery Electric Vehicle Technology for Medium- and Heavy-Duty Trucks.

Conventional diesel medium- and heavy-duty vehicles (MHDVs) create large amount of air emissions. With the advancement in technology and reduction in the cost of batteries, plug-in battery electric vehicles (BEVs) are increasingly attractive options for improving energy efficiency and reducing air emissions of MHDVs. In this paper, we compared the well-to-wheels (WTW) greenhouse gases (GHGs) and criteria air pollutant emissions of MHD BEVs with their conventional diesel counterparts across weight classes and vocations. We expanded the Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET) model to conduct the WTW analysis of MHDVs. The fuel economy for a wide range of MHDV weight classes and vocations, over various driving cycles, was evaluated using a high-fidelity vehicle dynamic simulation software (Autonomie). The environmental impacts of MHD BEVs are sensitive to the source of electricity used to recharge their batteries. The WTW results show that MHD BEVs significantly improve environmental sustainability of MHDVs by providing deep reductions in WTW GHGs, nitrogen oxides, volatile organic compounds, and carbon monoxide emissions, compared to conventional diesel counterparts. Increasing shares of renewable and natural gas technologies in future national and regional electricity generation are expected to reduce WTW particulate matters and sulfur oxide emissions for further improvement of the environmental performance of MHD BEVs.

Predictive Home Energy Management System With Photovoltaic Array, Heat Pump, and Plug-In Electric Vehicle

This article presents a predictive home energy management system (HEMS) for a residential building with integration of a plug-in electric vehicle (PEV), a photovoltaic array, and a heat pump. A stochastic model predictive control (MPC) strategy is applied in the HEMS in order to minimize the home's electricity cost and reduce the PEV battery degradation cost. Moreover, the MPC ensures that home load demand, PEV battery charging requirements, and household thermal comfort conditions are met. The MPC operates in real-time and thus minimizes the effects of gap between the forecasted and real data on the HEMS performance by updating its control decisions and the forecast data as the stochastic parameters are realized in each time step. The obtained simulation results demonstrate that the proposed control strategy reaches 96% to 97% of ideal performance achieved by off-line optimization counterpart with perfect data.