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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Gradient Architecture Design in Scalable Porous Battery Electrodes

Because it has been demonstrated to be effective toward faster ion diffusion inside the pore space, low-tortuosity porous architecture has become the focus in thick electrode designs, and other possibilities are rarely investigated. Here, to advance current understanding in the structure-affected electrochemistry and to broaden horizons for thick electrode designs, we present a gradient electrode design, where porous channels are vertically aligned with smaller openings on one end and larger openings on the other. With its 3D morphology carefully visualized by Raman mapping, the electrochemical properties between opposite orientations of the gradient electrodes are compared, and faster energy storage kinetics is found in larger openings and more concentrated active material near the separator. As further verified by simulation, this study on gradient electrode design deepens the knowledge of structure-related electrochemistry and brings perspectives in high-energy battery electrode designs.

25 ENERGY STORAGE↗
DOE OSTI2020

Fast Li-Ion Conductivity in Superadamantanoid Lithium Thioborate Halides

Lithium thioborates are promising fast Li-ion conducting materials, with similar properties to their lithium thiophosphate counterparts that have enabled the development of solid-state Li-ion batteries. By comparison, thioborates have scarcely been developed, however, offering new space for materials discovery. In this work, we report a new class of lithium thioborate halides that adopt a so-called supertetrahedral adamantanoid structure that houses mobile lithium ions and halide anions within interconnected 3D structural channels. Investigation of the structure using single-crystal XRD, neutron powder diffraction, and neutron PDF reveals significant lithium and halide anion disorder. The phases are non-stoichiometric, adopting slightly varying halide contents within the materials. These new superadamantanoid materials exhibit high ionic conductivities up to 1.4 mS cm -1 , which can be effectively tuned by the polarizability of the halide anion within the channels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Identifying Hidden Li–Si–O Phases for Lithium‐Ion Batteries via First‐Principle Thermodynamic Calculations

SiO–based materials are promising alloys and conversion‐type anode materials for lithium‐ion batteries and are recently found to be excellent dendrite‐proof layers for lithium‐metal batteries. However, only a small fraction of the Li–Si–O compositional space has been reported, significantly impeding the understanding of the phase transition mechanisms and the rational design of these materials both as anodes and as protection layers for lithium‐metal anodes. Herein, we identify three new thermodynamically stable phases within the Li–Si–O ternary system (Li 2 SiO 5 , Li 4 SiO 6, and Li 4 SiO 8 ) in addition to the existing records via first‐principle calculations. The electronic structure simulation shows that Li 2 SiO 5 and Li 4 SiO 8 phases are metallic in nature, ensuring high electronic conductivity required as electrodes. Moduli calculations demonstrate that the mechanical strength of Li–Si–O phases is much higher than that of lithium metal. The diffusion barriers of interstitial Li range from 0.1 to 0.6 eV and the interstitial Li hopping serves as the dominating diffusion mechanism in the Li–Si–O ternary systems compared with vacancy diffusion. These findings provide a new strategy for future discovery of improved alloying anodes for lithium‐ion batteries and offer important insight towards the understanding of the phase transformation mechanism of alloy‐type protection layers on lithium‐metal anodes.

Qu, Jiale↗
DOE OSTI2022

Real-space measurement of orbital electron populations for Li 1-x CoO 2

The operation of lithium-ion batteries involves electron removal from and filling into the redox orbitals of cathode materials, experimentally probing the orbital electron population thus is highly desirable to resolve the redox processes and charge compensation mechanism. Here, we combine quantitative convergent-beam electron diffraction with high-energy synchrotron powder X-ray diffraction to quantify the orbital populations of Co and O in the archetypal cathode material LiCoO 2 . The results indicate that removing Li ions from LiCoO 2 decreases Co t 2g orbital population, and the intensified covalency of Co–O bond upon delithiation enables charge transfer from O 2p orbital to Co e g orbital, leading to increased Co e g orbital population and oxygen oxidation. Theoretical calculations verify these experimental findings, which not only provide an intuitive picture of the redox reaction process in real space, but also offer a guidance for designing high-capacity electrodes by mediating the covalency of the TM–O interactions.

25 ENERGY STORAGE↗
DOE OSTI2023

Study on the Carbon Nanostructures for Nanosized Si Electrodes

Silicon (Si) has been considered as a next-generation anode material due to natural abundance, low operating potential (<0.5 V vs. Li/Li+), and high theoretical specific capacity of 4200 mAh g-1.[1] However, the electrochemical alloying reaction of Si involves large volume changes of 400% during lithiation and delithiation, causing cracking and pulverization of Si.[1] In addition, solid electrolyte interface (SEI) of Si anode experiences constant changes due to unstable SEI reactivity.[2] Considerable efforts have been made to design nanostructured Si materials to address the issues because nanostructuring can relieve the mechanical strain.[3] However, when compared to micrometer-sized active materials having sufficient electrolyte pathway through interparticle space, the nanoparticle (NP)-based electrodes tend to be densely packed. As mass loading is higher and electrode is thicker, ion transport issue can become more severe in the densely packed electrodes.[4] In this work, we will present studies on engineered porosity impacts performance in Si NP electrodes by altering carbon nanostructures. We explore the extreme limit of effectively non-porous electrodes using quasi-spherical, Si NPs, which result in densely packed electrodes when slurry is prepared with conventional carbon black. We engineer porosity using carbon nanostructures including multi-walled carbon nanotubes and carbon nanorods in place of conventional carbon black to create pore structure in Si NP-based electrodes. These experiments provide a correlation between mass loading, porosity and silicon utilization in Si NP-based electrodes. References: [1] C. K. Chan, H. Peng, G. Liu, K. Mcllwrath, X. F. Zhang, R. A. Huggins, Y. Cui, "High-performance lithium battery anodes using silicon nanowires", Nat. Nanotechnol., 2008, 3, 31, [2] J. D. McBrayer, M.-T. F. Rodrigues, M. C. Schulze, D. P. Abraham, C. A. Apblett, I. Bloom, G. M. Carroll, A. M. Coclasure, C. Fang, K. L. Harrison, G. Liu, S. D. Minteer, N. R. Neale, G. M. Veith, C. S. Johnson, J. T. Vaughey, A. K. Burrel, B. Cunningham, "Calendar aging of silicon-containing batteries", Nat. Energy, 2021, 6, 1164, [3] H. Wu, G. Zheng, N. Liu, T. J. Carney, Y. Yang, Y. Cui, "Engineering Empty space between Si Nanoparticles for Lithium-Ion Battery Anodes", Nano Lett., 2012, 12, 904, [4] X. Zhang, Z. Ju, Y. Zhu, K. J. Takeuchi, E. S. Takeuchi, A. C. Marschilok, G. Yu, "Multiscale Understanding and Architecture Design of High Energy/Power Lithium-Ion Battery Electrodes", Adv. Energy Mater., 2021, 11, 2000808

carbon nanostructure↗
DOE OSTI2022

Accelerating the discovery of battery electrode materials through data mining and deep learning models

The availability of crystalline materials databases allows for building accurate machine learning (ML) models that can accelerate the exploration of materials chemical space for energy storage applications. In this work, we screen all inorganic materials included in the Materials Project and AFLOW databases as potential metal-ion battery electrodes. We develop an efficient protocol to mine and screen raw data in current databases and provide a new database of electrode materials by considering pairs of charged and discharged electrodes. This effort leads to a new database with over 190,000 instances, in contrast to the original battery database which contains about 5000. The expanded battery data set is then used to build regression-based deep neural network models for predicting average voltages and percentage volume changes upon charging and discharging, which present improvements of at least 28% for target properties with respect to previous models, and are now able to predict anode electrodes (low voltage region) as well as electrodes that will not work in electrochemical cells (negative voltages), overcoming the challenges identified in previous ML models for battery electrodes. Additionally, a further screening of the expanded database itself allowed us to identify 35 novel electrode candidates with excellent battery performance metrics.

25 ENERGY STORAGE↗
DOE OSTI2020

Enumeration as a Tool for Structure Solution: A Materials Genomic Approach to Solving the Cation-Ordered Structure of Na 3 V 2 (PO 4 ) 2 F 3

While powder diffraction methods are routinely utilized to optimize structural models for compounds whose crystal structures are known, the determination of unknown structures is far more challenging. When the unknown structure is large, structure solution can become a virtually intractable problem using standard structure solution methodologies, especially when the space group cannot be unambiguously resolved. One such system is the promising Na-ion battery cathode material Na 3 V 2 (PO 4 ) 2 F 3 whose high temperature and room temperature structures were previously solved, but whose more complex low-temperature structure could not be determined. Here, a novel materials genomic approach is demonstrated for the solution of the unknown 100 K structure of Na 3 V 2 (PO 4 ) 2 F 3 in which enumeration methods are first used to generate a large number (~3,000) of trial structures based on plausible orderings of Na ions and then automated Rietveld refinements are carried out to optimize each of these trial structures. Based on both the analysis of the ensemble of optimized trial structures and the density functional theory energy minimization of selected trial structures, the 100 K structure of Na 3 V 2 (PO 4 ) 2 F 3 is best described as belonging to the space group A2 1 am with unit cell dimensions of a = 9.01928(4), b = 27.1379(1), c = 10.73307(5). The 100 K unit cell has a large volume of 2627.07(2) Å 3 with Z = 12 and 33 independent crystallographic sites (9 Na, 3 V, 3 P, 12 O, and 6 F) that is 3x and 6x larger than the room- and high-temperature polymorphs of this phase, respectively. Finally, the novel methods described here will be generally applicable for the solution of the complex cation-ordered structures that commonly occur for battery materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Experimental study on a novel three-phase absorption thermal battery with high energy density applied to buildings

Buildings contribute to 75% of total electricity consumption and 80% of peak electricity demand in the United States. A significant portion of building electricity consumption goes to space conditioning. Therefore, using thermal energy storage (TES) to decouple the building electricity consumption and the fluctuating space-conditioning load has significant potential to shift peak electricity demand and improve the stability of the grid. To provide effective TES within the spatial constraints in buildings, a three-phase absorption thermal battery (TATB) system with very high energy storage density was designed and studied. The TATB stores low-temperature heat in hydrate crystals of salts and supports space conditioning through absorption systems. In this study, a benchtop TATB using lithium chloride (LiCl) hydrate crystals as the storage material was tested under practical operating conditions for its energy storage density and discharge rate. We report the TATB successfully generated LiCl hydrate crystals during charging mode and then dissolved the crystals during discharging mode. A material-based energy storage density of 300 kWh/m 3 (specific energy of 903 kJ/kg) was achieved with a discharge rate of up to 1.3 kW thermal energy. The test results verified the high performance of the TATB and encouraged further development of this technology.

25 ENERGY STORAGE↗
DOE OSTI2023

Computational Investigation of MAX as Intercalation Host for Rechargeable Aluminum‐Ion Battery

Abstract Layered carbides and their analogs with MAX phase (general formula AM n+1 X n ) have emerged as promising candidates for energy storage and conversion applications. One frontier for energy storage is using MAX as an Al‐ion intercalation electrode. Given that many MAXs have Al as the A sites, the structure can potentially serve as a stable host for Al intercalation. Here in this work, 425 ternary MAX Al‐ion battery electrodes are computationally enumerated. Specifically, first principal phase diagram calculations are performed on the combinatorial space of 17 types of typical transition metals, five types of anions (C, N, B, Si, and P), three types of stoichiometries (n = 1, 2, and 3) and two types of layered stackings (α and β). Among all the ternary MAX materials, 44 candidates show reasonable synthetic accessibility, and six with extraordinary performance are predicted to be promising Al‐ion battery electrodes. With the phase stability, and electrochemical performance (average voltage, theoretical capacity, energy density, and Al diffusion barrier), the work provides a comprehensive computational assessment of the great opportunities behind MAX‐based Al‐ion batteries.

Chemistry↗
DOE OSTI2025

Data-driven design of electrolyte additives supporting high-performance 5 V LiNi 0.5 Mn 1.5 O 4 positive electrodes

LiNi 0.5 Mn 1.5 O 4 (LNMO) is a high-capacity spinel-structured material with an average lithiation/de-lithiation potential at ca. 4.6–4.7 V vs Li + /Li, far exceeding the stability limits of electrolytes. An efficient way to enable LNMO in lithium-ion batteries is to reformulate an electrolyte composition that stabilizes both graphitic (Gr) negative electrode with solid-electrolyte-interphase and LNMO with cathode-electrolyte-interphase. In this study, we select and test a diverse collection of 28 single and dual additives for the Gr||LNMO battery system. Subsequently, we train machine learning models on this dataset and employ the trained models to suggest 6 binary compositions out of 125, based on predicted final area-specific-impedance, impedance rise, and final specific-capacity. Such machine learning-generated new additives outperform the initial dataset. This finding not only underscores the efficacy of machine learning in identifying materials in a highly complicated application space but also showcases an accelerated material discovery workflow that directly integrates data-driven methods with battery testing experiments.

batteries↗
DOE OSTI2024

Physics-Guided Continual Learning for Predicting Emerging Aqueous Organic Redox Flow Battery Material Performance

Aqueous organic redox flow batteries (AORFBs) have gained popularity in renewable energy storage due to their low cost, environmental friendliness and scalability. The rapid discovery of aqueous soluble organic (ASO) redox-active materials necessitates efficient machine learning surrogates for predicting battery performance. The physics-guided continual learning (PGCL) method proposed in this study can incrementally learn data from new ASO electrolytes while addressing catastrophic forgetting issues in conventional machine learning. Using a AORFB database with a thousand potential materials generated by a 780 $\text{cm}^2$ interdigitated cell model, PGCL incorporates AORFB physics to optimize the continual learning task formation and training strategies to retain previously learned battery material knowledge. Finally, the trained PGCL demonstrates its capability in assessing emerging ASO materials within the established parameter space when evaluated with the dihydroxyphenazine isomers.

25 ENERGY STORAGE↗
DOE OSTI2021

Expanding the Ambient-Pressure Phase Space of CaFe 2 O 4 -Type Sodium Postspinel Host–Guest Compounds

CaFe 2 O 4 -type sodium postspinels (Na-CFs), with Na + occupying tunnel sites, are of interest as prospective battery electrodes. While many compounds of this structure type require high-pressure synthesis, several compounds are known to form at ambient pressure. Here we report a large expansion of the known Na-CF phase space at ambient pressure, having successfully synthesized NaCrTiO 4 , NaRhTiO 4 , NaCrSnO 4 , NaInSnO 4 , NaMg 0.5 Ti 1.5 O 4 , NaFe 0.5 Ti 1.5 O 4 , NaMg 0.5 Sn 1.5 O 4 , NaMn 0.5 Sn 1.5 O 4 , NaFe 0.5 Sn 1.5 O 4 , NaCo 0.5 Sn 1.5 O 4 , NaNi 0.5 Sn 1.5 O 4 , NaCu 0.5 Sn 1.5 O 4 , NaZn 0.5 Sn 1.5 O 4 , NaCd 0.5 Sn 1.5 O 4 , NaSc 1.5 Sb 0.5 O 4 , Na 1.16 In 1.18 Sb 0.66 O 4 , and several solid solutions. In contrast to earlier reports, even cations that are strongly Jahn–Teller active (e.g., Mn 3+ and Cu 2+ ) can form Na-CFs at ambient pressure when combined with Sn 4+ rather than with the smaller Ti 4+ . Order and disorder are probed at the average and local length-scales with synchrotron powder X-ray diffraction and solid-state NMR spectroscopy. Strong ordering of framework cations between the two framework sites is not observed, except in the case of Na 1.16 In 1.18 Sb 0.66 O 4 . This compound is the first example of an Na-CF that contains Na + in both the tunnel and framework sites, reminiscent of Li-rich spinels. Trends in the thermodynamic stability of the new compounds are explained on the basis of crystal-chemistry and density functional theory (DFT). Further DFT calculations examine the relative stability of the CF versus spinel structures at various degrees of sodium extraction in the context of electrochemical battery reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Accurate Prediction of Voltage of Battery Electrode Materials Using Attention-Based Graph Neural Networks

Performing first-principles calculations to discover electrodes’ properties in the large chemical space is a challenging task. While machine learning (ML) has been applied to effectively accelerate those discoveries, most of the applied methods ignore the materials’ spatial information and only use predefined features: based only on chemical compositions. Here, we propose two attention-based graph convolutional neural network techniques to learn the average voltage of electrodes. Our proposed methods, which combine both atomic composition and atomic coordinates in 3D-space, improve the accuracy in voltage prediction significantly when compared to composition-based ML models. The first model directly learns the chemical reaction of electrodes and metal ions to predict their average voltage, whereas the second model combines electrodes’ ML predicted formation energy (E form ) to compute their average voltage. Our E form -based model demonstrates improved accuracy in transferability from our subset of learned Li ions to Na ions. Moreover, we predicted the theoretical voltage of 10 Na x MPO 4 F (M = Ti, Cr, Fe, Cu, Mn, Co, and Ni) fluorophosphate battery frameworks, which are unavailable in the Material Project database. It could be shown that we can expect average voltages higher than 3.1 V from those Na battery frameworks except from the NaTiPO 4 F and TiPO 4 F pair of electrodes, which offer an average voltage of 1.32 V.

25 ENERGY STORAGE↗
DOE OSTI2025

Field Test and Thermal Performance Comparison of a Novel Underground Thermal Battery with a Single U-tube Borehole Heat Exchanger for Geothermal Heat Pump Application

Geothermal Heat Pumps (GHP) are a proven technology to electrify and decarbonize space heating and cooling by utilizing the thermally consistent underground as a heat sink or source. However, the high drilling costs of conventional borehole heat exchangers (BHEs) associated with GHP systems and subsurface heterogeneity have been two major challenges to their widespread adoption. In this paper, we present results from a field-scale pilot of an Underground Thermal Battery (UTB) as a potential alternative to a conventional BHE. To benchmark the UTB performance, a side-by-side field test was conducted to compare the UTB with a conventional BHE installed at the same site. The UTB was installed in a 7.01-meter-deep borehole having a diameter of 0.9 meter, whereas the conventional BHE (with single U-tube loop) is in a borehole with 36.6-meter depth and 0.15-meter diameter. Both are integrated into a GHP system to meet the thermal energy demands of office space at the Illinois Energy Farm on the University of Illinois Urbana-Champaign campus. The system’s performance is compared in terms of heat transfer rate, outlet temperatures, and contributions to the overall thermal power of the GHP system under varying thermal demands and in different heat pump operation modes: heating only, cooling only, and hybrid (alternative, diurnal heating and cooling). Results to date indicate that the UTB delivers a more consistent response under during a time period of varying thermal demands. Its operational performance is better during short-term with higher thermal demands, while the conventional BHE performs better under continuous, long-term thermal demands.

Pokhrel, Sajjan [ORNL] (ORCID:0000000228523749)↗
DOE OSTI2020

Mobile Sorption-based Thermal Battery for Harvesting Low-Temperature Geothermal Energy

Around 20% of the total primary energy in the United States is consumed for thermal demands of buildings such as space cooling, dehumidification, and space heating (EIA 2018). Low-temperature geothermal energy is abundant and can effectively satisfy buildings’ thermal demands. However, low-temperature geothermal energy is underutilized because the energy density of geothermal fluid is too low to justify the costs associated with transporting it between existing geothermal resources and buildings. The mobile sorption-based thermal battery (MSTB) system has been developed using three-phase (i.e., vapor–liquid, solution–solid, crystal) sorption technology to harvest low-temperature heat and store it with a much higher energy density than the geothermal fluid. The energy density of salt crystals is over six times higher than geothermal fluid, which makes long-distance transportation of salt crystals economically feasible. Salt crystals can be used to dehumidify air or provide space cooling in buildings, which alleviates peak demand on the electricity grid by offsetting electricity use for these end uses. This helps improve the grid’s stability and resilience. High-energy storage density, fast crystallization, and dissolution of salt crystals are all critical to the viability and performance of the MSTB system. Therefore, the design and operation of MSTB systems need to ensure effective generation and dissolution of salt crystals inside the MSTB. To achieve this target, this seedling project developed an experimental apparatus for characterizing the crystallization and dissolution processes. The energy density and potential latent cooling capacity of the MSTB are also evaluated based on lab test results. The crystallization results showed that the generated lithium chloride hydrate crystals are fluffy, the crystallization process lasts about 50 min, and the maximum crystal fraction (i.e., the ratio of crystal mass to the mass in the MSTB) can be up to 51.1% of the total mass in the MSTB at a solution flow rate of 1.58 g/s. The dissolution results show that the salt crystals in the MSTB can be fully dissolved within 15–28 min, based on different test conditions. Reducing solution flow rate and cooling water temperature can achieve increased energy storage density and crystal fraction. While the increase in the discharge rate (i.e., latent cooling capacity for dehumidifying air) is achieved by increasing flow rate and temperature of inlet diluted solution, as well as by using a pump for internal solution circulation, the discharge rate increases by 38%, from 0.95 kW to 1.31 kW. Compared with increasing the inlet solution flow rate, power consumption of salt solution transportation can be reduced by using a pump for internal solution circulation. The crystallization test results also showed that the maximum energy storage density is 981.8 kJ/kg, and the maximum discharge rate of the dissolution tests is ≤1.79 kW. Both are above the target values of 900 kJ/kg and 1.75 kW) for this project. The work reported here proves the feasibility and advancement of the MSTB system, which is helpful to the further study and improvement of the MSTB system.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Coupling of multiscale imaging analysis and computational modeling for understanding thick cathode degradation mechanisms

Here, using a thick NMC811 (LiNi 0.8 Mn 0.1 Co 0.1 O 2 ) electrode as an example, we present a macro- to nanoscale 2D and 3D imaging analysis approach coupled with 4D (space + time) computational modeling to probe its degradation mechanism in a lithium-ion battery cell. Particle cracking increases and contact loss between particles and carbon-binder domain are observed to correlate with the cell degradation. This study unravels that the reaction heterogeneity within the thick cathode caused by the unbalanced electron conduction is the main cause of the battery degradation over cycling. The increased heterogeneity in the system will entail more cathode regions where the degree of active material utilization is uneven, leading to higher probabilities of particle cracking. These findings shed light on the crucial role of the electronic and ionic transportation networks in the performance deterioration of the thick cathode. They also provide guidance for cathode architecture optimization and performance improvement.

25 ENERGY STORAGE↗
DOE OSTI2024

MODAQ-BB (Modular Offshore Data Acquisition System - Blackbox) [SWR-24-72]

MODAQ-BB is a compact, rapid deployment data acquisition system that can withstand water depths up to 400m. Codenamed "BlackBox" (or simply BB), since its initial purpose was to track marine assets and record vital data streams that could later be recovered in the event of a mishap - much like a traditional black box used in aviation and shipping, the name has stuck. MODAQ BlackBox is a battery-operable microcontroller platform with internal inertial sensing, GPS, satellite communications, and additional I/O (input/output) support in a depth-rated pressure enclosure. Since BB is self-contained and relatively compact, it can be quickly deployed with minimal effort. The enclosure can be clamped to a tube (such as part of a railing) or mast in a location with unobstructed view of the sky using the available clamp accessory or a common hose clamp. While BB is designed to operate unattended, users can configure what data are uploaded and the frequency of satellite transmissions. Once data are uploaded, they can be relayed to an email distribution list, the MODAQ:Web operational dashboard, or a custom destination. BB has found utility in the National Laboratory of the Rockies' (NLR's) Waterpower projects beyond its original vision and has been configured and successfully deployed in more traditional data-gathering applications where a simple, battery-operated solution was indicated. As part of the MODAQ family, BB fills a space in the spectrum of missions that can be supported that were previously impractical using the traditional MODAQ hardware architecture due to factors such as weight, size, and cost.

Raye, Robert↗
DOE OSTI2020

Modeling charging infrastructure impact on the electric vehicle market in China

The plug-in electric vehicle (PEV) is deemed as a critical technological revolution, and the governments are imposing various vehicle policies to promote its development. Meanwhile, the market success of PEVs depends on many aspects. The study reported herein integrates one’s use of charging infrastructure at home, public place and workplace into the market dynamics analysis tool, New Energy and Oil Consumption Credits (NEOCC) model, to systematically assess the charging infrastructure (home parking ratio, public charging opportunity, and charging costs) impact on PEV ownership costs and analyze how the PEV market shares may be affected by the attributes of the charging infrastructure. Compared to the charging infrastructure, the impact of battery costs is incontrovertibly decisive on PEV market shares, the charging infrastructure is still non-negligible in the PEV market dynamics. The simulation results find that the public charging infrastructure has more effectiveness on promoting the PEV sales in the PEV emerging market than it does in the PEV mature market. However, the improvement of charging infrastructure does not necessarily lead to a larger PEV market if the charging infrastructure incentives do not coordinate well with other PEV policies. Besides, the increase of public charging opportunities has limited motivations on the growth of public PEV fleets, which are highly correlated to the number of public fast charging stations or outlets. It also finds that more home parking spaces can stimulate more sales of personal plug-in hybrid electric vehicles instead of personal battery electric vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗