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Pesaran, A

Publications and source records attributed to Pesaran, A.

Techno-Economic Analysis of BEV Service Providers Offering Battery Swapping Services: Preprint

Battery electric vehicles (BEVs) offer the potential to reduce both oil imports and greenhouse gas emissions, but high upfront costs, battery-limited vehicle range, and concern over high battery replacement costs may discourage potential buyers. A subscription model in which a service provider owns the battery and supplies access to battery swapping infrastructure could reduce upfront and replacement costs for batteries with a predictable monthly fee, while expanding BEV range. Assessing the costs and benefits of such a proposal are complicated by many factors, including customer drive patterns, the amount of required infrastructure, battery life, etc. The National Renewable Energy Laboratory has applied its Battery Ownership Model to compare the economics and utility of BEV battery swapping service plan options to more traditional direct ownership options. Our evaluation process followed four steps: (1) identifying drive patterns best suited to battery swapping service plans, (2) modeling service usage statistics for the selected drive patterns, (3) calculating the cost-of-service plan options, and (4) evaluating the economics of individual drivers under realistically priced service plans. A service plan option can be more cost-effective than direct ownership for drivers who wish to operate a BEV as their primary vehicle where alternative options for travel beyond the single-charge range are expensive, and a full-coverage-yet-cost-effective regional infrastructure network can be deployed. However, when assumed cost of gasoline, tax structure, and absence of purchase incentives are factored in, our calculations show the service plan BEV is rarely more cost-effective than direct ownership of a conventional vehicle.

25 ENERGY STORAGE↗

Accelerating Development of EV Batteries Through Computer-Aided Engineering (Presentation)

The Department of Energy's Vehicle Technology Program has launched the Computer-Aided Engineering for Automotive Batteries (CAEBAT) project to work with national labs, industry and software venders to develop sophisticated software. As coordinator, NREL has teamed with a number of companies to help improve and accelerate battery design and production. This presentation provides an overview of CAEBAT, including its predictive computer simulation of Li-ion batteries known as the Multi-Scale Multi-Dimensional (MSMD) model framework. MSMD's modular, flexible architecture connects the physics of battery charge/discharge processes, thermal control, safety and reliability in a computationally efficient manner. This allows independent development of submodels at the cell and pack levels.

25 ENERGY STORAGE↗

Battery Ownership Model: A Tool for Evaluating the Economics of Electrified Vehicles and Related Infrastructure; Preprint

Electric vehicles could significantly reduce greenhouse gas (GHG) emissions and dependence on imported petroleum. However, for mass adoption, EV costs have historically been too high to be competitive with conventional vehicle options due to the high price of batteries, long refuel time, and a lack of charging infrastructure. A number of different technologies and business strategies have beenproposed to address some of these cost and utility issues: battery leasing, battery fast-charging stations, battery swap stations, deployment of charge points for opportunity charging, etc. In order to investigate these approaches and compare their merits on a consistent basis, the National Renewable Energy Laboratory (NREL) has developed a new techno-economic model. The model includes ninemodules to examine the levelized cost per mile for various types of powertrain and business strategies. The various input parameters such as vehicle type, battery, gasoline, and electricity prices; battery cycle life; driving profile; and infrastructure costs can be varied. In this paper, we discuss the capabilities of the model; describe key modules; give examples of how various assumptions,powertrain configurations, and business strategies impact the cost to the end user; and show the vehicle's levelized cost per mile sensitivity to seven major operational parameters.

25 ENERGY STORAGE↗

Accelerating Battery Design Using Computer-Aided Engineering Tools: Preprint

Computer-aided engineering (CAE) is a proven pathway, especially in the automotive industry, to improve performance by resolving the relevant physics in complex systems, shortening the product development design cycle, thus reducing cost, and providing an efficient way to evaluate parameters for robust designs. Academic models include the relevant physics details, but neglect engineeringcomplexities. Industry models include the relevant macroscopic geometry and system conditions, but simplify the fundamental physics too much. Most of the CAE battery tools for in-house use are custom model codes and require expert users. There is a need to make these battery modeling and design tools more accessible to end users such as battery developers, pack integrators, and vehicle makers.Developing integrated and physics-based CAE battery tools can reduce the design, build, test, break, re-design, re-build, and re-test cycle and help lower costs. NREL has been involved in developing various models to predict the thermal and electrochemical performance of large-format cells and has used in commercial three-dimensional finite-element analysis and computational fluid dynamics tostudy battery pack thermal issues. These NREL cell and pack design tools can be integrated to help support the automotive industry and to accelerate battery design.

25 ENERGY STORAGE↗