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At least 73 records · Page 4

Comprehensive Total Cost of Ownership Quantification for Vehicles with Different Size Classes and Powertrains

In order to accurately compare the costs of two vehicles, the total cost of ownership (TCO) should consist of all costs related to both purchasing and operating the vehicle. This TCO analysis builds on previous work to provide a comprehensive perspective of all relevant vehicle costs of ownership. In this report, we present what we believe to be the most comprehensive explicit financial analysis of the costs that will be incurred by a vehicle owner. This study considers vehicle cost and depreciation, financing, fuel costs, insurance costs, maintenance and repair costs, taxes and fees, and other operational costs to formulate a holistic total cost of ownership and operation of multiple different vehicles. For each of these cost parameters that together constitute a comprehensive TCO, extensive literature review and data analysis were performed to find representative values in order to build a holistic TCO for vehicles of all size classes. The light- and heavy-duty vehicles selected for analysis in this report are representative of those that are on the road today and expected to be available in the future. Important additive analyses in this study include systematic analysis of vehicle depreciation, in-depth examination of insurance premium costs, comprehensive maintenance and repair estimates, analysis of all relevant taxes and fees, and considerations of specific costs applicable to commercial vehicles. We find that cars depreciate faster than light trucks and that older plug-in electric vehicles have a greater depreciation rate than newer electric vehicles. Light-duty vehicle (LDV) insurance costs show comparable costs for different powertrains, and lower costs for larger size classes. Medium- and heavy-duty vehicle (MHDV) insurance costs vary significantly by vocation. Electric and electrified powertrains have lower maintenance and repair costs than internal combustion engine (ICE) powertrains for all vehicle sizes, relative to vehicle price. MHDV maintenance and repair costs depend heavily on vocation and duty cycle. LDV taxes and fees are comparable across powertrain types and size classes, though marginally higher registration fees exist for alternative fuel vehicles. MHDV fees depend on the vocation, weight rating, and state. Many electric tractor trailers would be affected by additional battery weight, reducing the available payload capacity, and this cost can be substantial. Electric vehicle charging for commercial vehicles can be time-consuming; labor rates can cause this cost to dominate TCO. With improved knowledge of each of the cost components, we calculate a lifetime TCO for comparison across vehicles of different types and attributes. For a simulated small sport utility vehicle in 2025, modeled using Autonomie, the hybrid electric vehicle (HEV) has the lowest cost, followed by the conventional ICE vehicle. For MHDV, TCO can be drastically different depending on the vocation. Long-haul vehicles typically have the lowest per-mile costs. Excluding labor costs, the class 4 delivery has a comparable TCO to the day cab. Vocational trucks, refuse trucks, and transit buses have a high per-mile cost of ownership due to maintenance and insurance. For all of these vehicles, the cost of operating the vehicle is heavily weighted by the labor of the driver, followed by the fuel costs. While the HEV begins as the lowest cost powertrain for passenger vehicles, fuel cells are forecast to reach cost parity by 2030 when hydrogen prices reach $\$ 5$/kg while battery electric vehicles (BEV) reach cost parity by 2035 at a battery cost of $\$ 98$ per usable kWh of capacity, with these two technologies being the lowest cost in 2050. For the class 8 day cab tractor, the HEV and ICE vehicle begin as the lowest cost powertrains, and the 250-mile BEV reduces in cost from the most expensive to the least expensive by 2030.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Alternative Fuel Vehicle Usage and Owner Demographics in New York State

With mounting concerns over climate change and the environmental impact of fossil fuels, the United States has witnessed a growing interest in alternative fuel vehicles (AFVs). In 2021, approximately 1.5 million battery EVs (BEVs), 0.8 million plug-in hybrid EVs (PHEVs), and 5.5 million hybrid EVs (HEVs) were registered in the United States. In the state of New York, a total of 51,900 BEVs, 44,600 PHEVs, and 221,600 HEVs were registered in 2021. The current report presents the results of an analysis of AFV adoption patterns in New York State and the rest of the United States based on data from the 2017 National Household Travel Survey (NHTS). Overall, the report reveals the demographics and mobility factors (e.g., household income, homeownership, and trip length) that contribute to the adoption of AFVs. This study provides insights that can inform policy decisions aimed at promoting sustainable transportation solutions.The 2017 NHTS data showed that the percentage of households owning at least one AFV is lower in New York City compared with that in other regions of New York State. From the NHTS samples, of the 25 households that owned at least one BEV in New York State, 15 households (60%) lived within a 5-mile radius, based on the great circle distance, of the nearest charging station, and 23 households (92%) lived within a 10-mile radius of the nearest charging station. Furthermore, among the 40 households in New York State that own at least one PHEV, 48% (19 households) lived within a 5-mile radius of the closest EV charging station, and 83% (33 households) lived within a 10-mile radius of the nearest charging station. The rest of the United States had a higher percentage of households that own at least one AFV compared with that of New York State. A comparison was made between EV adoption levels using NHTS and EValuateNY, which is a tool that gathers statistics on the electric car market in New York State. The estimates obtained from New York State household samples in NHTS were slightly lower than the data provided by EValuateNY. In New York State and the rest of the United States, households with higher incomes tended to have a higher proportion of AFV ownership compared with those with lower incomes. For example, households in New York State earning $\$ $150,000 or more had an approximately 6% share of owning at least one AFV, which was markedly higher than those earning less than $\$ $100,000 (less than 3%). Additionally, homeowners in New York State and the rest of the United States also exhibited a significantly higher share of AFV ownership compared with that of renters. In New York State, households that own at least one AFV tended to travel farther and had longer travel times compared with their counterparts without an AFV. In terms of households with at least one AFV, households with HEVs tended to have more person trips, longer person miles of travel, and more vehicle miles traveled, resulting in longer travel times than that of households with BEVs or PHEVs. Notably, households with AFVs had a slightly lower share of family and personal business trips but a higher share of social and recreational trips compared with households without AFVs. Additionally, households with at least one AFV tended to have a slightly higher share of walking trips than their counterparts without an AFV. However, the comparisons were not statistically significant. These travel patterns observed in New York State were consistent with those observed in other regions of the United States.

33 ADVANCED PROPULSION SYSTEMS↗

Optimizing and Diversifying the Electric Range of Plug-in Hybrid Electric Vehicles for U.S. Drivers

To provide useful information for automakers to design successful plug-in hybrid electric vehicle (PHEV) products and for energy and environmental analysts to understand the social impact of PHEVs, this paper addresses the question of how many of the U.S. consumers, if buying a PHEV, would prefer what electric ranges. The Market-oriented Optimal Range for PHEV (MOR-PHEV) model is developed to optimize the PHEV electric range for each of 36,664 sampled individuals representing U.S. new vehicle drivers. The optimization objective is the minimization of the sum of costs on battery, gasoline, electricity and refueling hassle. Assuming no battery subsidy, the empirical results suggest that: 1) the optimal PHEV electric range approximates two thirds of one s typical daily driving distance in the near term, defined as $450/kWh battery delivered price and $4/gallon gasoline price. 2) PHEVs are not ready to directly compete with HEVs at today s situation, defined by the $600/kWh battery delivered price and the $3-$4/gallon gasoline price, but can do so in the near term. 3) PHEV10s will be favored by the market over longer-range PHEVs in the near term, but longer-range PHEVs can dominate the PHEV market if gasoline prices reach as high as $5-$6 per gallon and/or battery delivered prices reach as low as $150-$300/kWh. 4) PHEVs can become much more attractive against HEVs in the near term if the electric range can be extended by only 10% with multiple charges per day, possible with improved charging infrastructure or adapted charging behavior. 5) the impact of a $100/kWh decrease in battery delivered prices on the competiveness of PHEVs against HEVs can be offset by about $1.25/gallon decrease in gasoline prices, or about 7/kWh increase in electricity prices. This also means that the impact of a $1/gallon decrease in gasoline prices can be offset by about 5/kWh decrease in electricity prices.

02 PETROLEUM↗

A free-trailing vane flow direction indicator employing a linear output Hall effect transducer

The Hall effect vane (HEV) was developed to measure flow angularity in the NASA 40-by-80-foot and 80-by-120-foot wind tunnels. This indicator is capable of sensing flow direction at air speeds from 5 to 300 knots and over a + or - 40 deg angle range with a resolution of 0.1 deg. A free-trailing vane configuration employing a linear output Hall effect transducer as a shaft angle resolver was used. The current configuration of the HEV is designed primarily for wind tunnel calibration testing; however, other potential applications include atmospheric, flight or ground research testing. The HEV met initial design requirements.

Zell, Peter T.↗

Navigation API Route Fuel Saving Opportunity Assessment on Large-Scale Real-World Travel Data for Conventional Vehicles and Hybrid Electric Vehicles: Preprint

The green routing strategy instructing a vehicle to select a fuel-efficient route benefits the current transportation system with fuel-saving opportunities. This paper introduces a navigation API route fuel-saving evaluation framework for estimating fuel advantages of alternative API routes based on large-scale, real-world travel data for conventional vehicles (CVs) and hybrid electric vehicles (HEVs). The navigation APIs, such Google Directions API, integrate traffic conditions and provide feasible alternative routes for origin-destination pairs. This paper develops two link-based fuel-consumption models stratified by link-level speed, road grade, and functional class (local/non-local), one for CVs and the other for HEVs. The link-based fuel-consumption models are built by assigning travel from a large number of GPS driving traces to the links in TomTom MultiNet as the underlying road network layer and road grade data from a U.S. Geological Survey elevation data set. Fuel consumption on a link is calculated by the proposed fuel consumption model. This paper envisions two kinds of applications: 1) identifying alternate routes that save fuel, and 2) quantifying the potential fuel savings for large amounts of travel. An experiment based on a large-scale California Household Travel Survey GPS trajectory data set is conducted. The fuel consumption and savings of CVs and HEVs are investigated. At the same time, the trade-off between fuel saving and time saving for choosing different routes is also examined for both powertrains.

33 ADVANCED PROPULSION SYSTEMS↗

Real time trajectory optimization for hybrid energy management utilizing connected information technologies

The disclosure is directed to solving a full trajectory optimization problem in real-time for a hybrid electric vehicle (HEV) such that future driving conditions and energy usage may be fully considered in determining optimal engine energy usage and battery energy usage in real-time during a trip. An electronic control unit of the HEV may be configured to: receive route information for a route to be driven by the HEV; and after receiving the route information, iterating the operations of: measuring a current state of charge (SOC) of the battery; using at least the measured SOC and an initial co-state value stored in a memory, performing a process to iteratively update the co-state value to obtain an updated co-state value; using at least the updated co-state value, computing an updated control value; and applying the updated control value to control a usage of the battery and the internal combustion engine.

Huang, Mike X.↗

Pareto Efficient Policy for Supervisory Power Management Control

n this paper we address the problem of online optimization of the supervisory power management control in parallel hybrid electric vehicles (HEVs). We model HEV opera- tion as a controlled Markov chain using the long-run expected average cost per unit time criterion, and we show that the control policy yielding the Pareto optimal solution minimizes the average cost criterion online. The effectiveness of the proposed solution is validated through simulation and compared to the solution derived with dynamic programming using the average cost criterion.

Markov chain↗

A Multiobjective Optimization Framework for Online Stochastic Optimal Control in Hybrid Electric Vehicles

The increasing urgency to extract additional efficiency from hybrid propulsion systems has led to the development of advanced power management control algorithms. In this paper we address the problem of online optimization of the supervisory power management control in parallel hybrid electric vehicles (HEVs). We model HEV operation as a controlled Markov chain and we show that the control policy yielding the Pareto optimal solution minimizes online the long-run expected average cost per unit time criterion. The effectiveness of the proposed solution is validated through simulation and compared to the solution derived with dynamic programming using the average cost criterion. Both solutions achieved the same cumulative fuel consumption demonstrating that the online Pareto control policy is an optimal control policy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

CuS and Cu 2 S as Cathode Materials for Lithium Batteries: A Review [A Review on CuS and Cu 2 S as Cathode Materials for Lithium Batteries]

Nowadays, lithium-ion batteries (LIBs) take a very important role for energy storage. LIBs are dominant in consumer electronics, and they have also entered the market of hybrid electric vehicles (HEVs), plug-in HEVs, and pure EVs. However, state-of-the-art LIBs are electrochemically intercalation-based and are still limited in energy density and power rates. To address these challenges and others (e. g. safety issues and cost), conversion-based copper sulfides (Cu x S, 1≤x≤2) have been investigated as alternative cathodes for improved electrochemical performance, that is, higher energy density, better cycling stability, and enhanced rate capability. In this paper, we summarize the recent research progress on Cu x S to gain a better understanding of the material's electrochemical mechanisms and develop feasible strategies for improving its performance.

25 ENERGY STORAGE↗

Repurposing of Batteries from Electric Vehicles

Energy storage for stationary use is gaining traction both at the grid scale and distributed level. As renewable energy generation increases, energy storage is needed to compensate for the volatility of renewable over various time scales. This requires energy storage that is tailored for various energy to power (E/P) ratios. Other applications for energy storage include peak shaving, time shifting, load leveling, VAR control, frequency regulation, spinning reserves and other ancillary applications. While the need for energy storage for stationary applications is obvious, the regulations that determine the economic value of adding storage are at various stages of development. This has created a reluctance on the part of energy storage manufacturers to develop a suite of storage systems that can address the myriad of applications associated with stationary applications. Deployment of battery energy storage systems in the transportation sector is ahead of the curve with respect to the stationary space. Batteries, along with battery management systems (BMS) have been deployed for hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs) and electric vehicles (EVs). HEVs have now been deployed for 12 years, while PHEVs for 8 and EVs for 4 years. Some of the batteries are approaching end of life within the vehicle, and are ready to be taken off for recycling and disposal. Performance within a vehicle is non-negotiable in terms of miles traveled per charge, resulting in the batteries retaining a significant portion of their life. For stationary applications, the remaining energy and power of the battery can still be used by grouping together a few of these batteries. This enables getting the most of these batteries, while ensuring that performance is not compromised in either the automotive or stationary applications. This work summarizes the opportunities for such re-purposing of automotive batteries, along with the advantages and limitations

battery management systems↗

Cost Analysis of Plug-In Hybred Electric Vehicles Using GPS-Based Longitudinal Travel Data

Using spatial, longitudinal travel data of 415 vehicles over 3 18 months in the Seattle metropolitan area, this paper estimates the operating costs of plug-in hybrid electric vehicles (PHEVs) of various electric ranges (10, 20, 30, and 40 miles) for 3, 5, and 10 years of payback period, considering different charging infrastructure deployment levels and gasoline prices. Some key findings were made. (1) PHEVs could help save around 60% or 40% in energy costs, compared with conventional gasoline vehicles (CGVs) or hybrid electric vehicles (HEVs), respectively. However, for motorists whose daily vehicle miles traveled (DVMT) is significant, HEVs may be even a better choice than PHEV40s, particularly in areas that lack a public charging infrastructure. (2) The incremental battery cost of large-battery PHEVs is difficult to justify based on the incremental savings of PHEVs operating costs unless a subsidy is offered for largebattery PHEVs. (3) When the price of gasoline increases from $4/gallon to $5/gallon, the number of drivers who benefit from a larger battery increases significantly. (4) Although quick chargers can reduce charging time, they contribute little to energy cost savings for PHEVs, as opposed to Level-II chargers.

Wu, Xing↗

Modeling electric vehicle adoption considering a latent travel pattern construct and charging infrastructure

This paper presents a behavioral model of public, revealed preferences (RP) for various types of electric vehicles (EVs) while accounting for a latent (green) travel pattern construct and charging infrastructure characteristics. Specifically, a two-level nested logit (NL) model is estimated to explain households' fuel type choice among five alternatives and three nests: (1) battery electric vehicles (BEVs); (2) hybrid vehicles including hybrid electric vehicles (HEVs) and plug-in HEVs (PHEVs); and (3) conventional vehicles including gasoline and diesel vehicles. Further, a latent travel pattern construct which captures a week-long number of trips by non-vehicle travel modes as well as daily vehicle and tollway use is estimated in a structural equation setting and subsequently fed into the NL model. Using a recent RP dataset from the California Household Travel Survey, we identify market segments for alternative fuel types based on households' socio-economic characteristics, built environment factors concerning public plug-in EV (PEV) charging infrastructure characteristics, latent and observable travel behavior factors of a household vehicle's principal driver, and vehicle attributes. The results highlight that the number of public PEV charging stations is only significant for households choosing PHEVs and interestingly insignificant in the BEV utility. Furthermore, the sensitivity analysis of the findings reveals that PHEV users are elastic with respect to household vehicle ownership ratio and the latent green travel pattern construct, while BEV users are inelastic to any explanatory variable.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Ni/Li Disordering in Layered Transition Metal Oxide: Electrochemical Impact, Origin, and Control

Lithium-ion batteries (LIBs) not only power most of today’s hybrid electric vehicles (HEV) and electric vehicles (EV) but also are considered as a very promising system for grid-level storage. Large-scale applications for LIBs require substantial improvement in energy density, cost, and lifetime. Layered Li(NixMnyCoz)O2 (NMC, x+y+z=1) materials from solid-solution approaches to LiMO2 (M = Ni, Mn, Co, etc) are the most promising candidates for their high reversible capacity, better environmental compatibility, and lower cost compared with the traditional LiCoO2. In order to further boost Li storage capacity, a great deal of attention has been directed toward developing Ni-rich NMCs. However, structural disorder as a result of Ni/Li exchange in octahedral sites becomes a critical issue when Ni content increases to high values, as it leads to a detrimental effect on Li diffusivity, cycling stability, first-cycle efficiency, and overall electrode performance. Increasing efforts have been dedicated to improving the electrochemical performance of NMC materials via reduction of cationic mixing. Therefore, it is important to summarize this research field and provide in-depth insight into impact of Ni/Li disorder on electrochemical characteristics in layered NMC materials and its origin to accelerate the future development of NMC materials with high performance. In this Account, we start by analyzing the impact of Ni/Li disorder on electrochemical characteristics in layered NMC materials. The antisite Ni in the Li layer can limit the rate performance by impeding the Li-ion transport. It will also degrade the cycling stability by inducing the anisotropic stress in the bulk structure. Nevertheless, the antisite Ni-ions don’t always bring drawbacks to the electrochemical performance, some studies including our works found that it can improve the thermal stability and the cycling structure stability of Ni-rich NMC materials. We next discussed the driving forces and the kinetic advantages accounting for the Ni/Li exchange and summarized that the steric effect of cation size and the magnetic interactions between TM cations are the two main driving forces to promote the Ni/Li exchange during synthesis procedure and the electrochemical cycling, and the low energy barrier of Ni2+ migration from the 3a site in TM layer to 3b site in Li layer further provides the kinetic advantage. Based on above understandings, we reviewed the progress made to control the Ni/Li disorder and summarized three main ways: (i) suppressing the driving force from the steric effect by ion exchange; (ii) tuning the magnetic interaction by cationic substitution; (iii) kinetic controlling of Ni migration. Finally, our brief outlooks on the future development of controlling the Ni/Li disorder in NMC materials are provided. It is believed that this Account will provide significant understanding and inspirations toward developing high-performance NMC materials with controlled Ni/Li disorder.

Zheng, Jiaxin↗

A native IgE in complex with profilin provides insights into allergen recognition and cross-reactivity

Allergies have become a rising health problem, where plentiful substances can trigger IgE-mediated allergies in humans. While profilins are considered minor allergens, these ubiquitous proteins are primary molecules involved in cross-reactivity and pollen-food allergy syndrome. Here we report the first crystal structures of murine Fab/IgE, with its chains naturally paired, in complex with the allergen profilin from Hevea brasiliensis (Hev b 8). The crystallographic models revealed that the IgE’s six complementarity-determining regions (CDRs) interact with the allergen, comprising a rigid paratope-epitope surface of 926 Å 2 , which includes an extensive network of interactions. Interestingly, we also observed previously unreported flexibility at Fab/IgE’s elbow angle, which did not influence the shape of the paratope. The Fab/IgE exhibits a high affinity for Hev b 8, even when using 1 M NaCl in BLI experiments. Finally, based on the encouraging cross-reactivity assays using two mutants of the maize profilin (Zea m 12), this antibody could be a promising tool in IgE engineering for diagnosis and research applications.

59 BASIC BIOLOGICAL SCIENCES↗

Closed‐loop hierarchical control strategies for connected and autonomous hybrid electric vehicles with random errors

This study presents a closed‐loop hierarchical control strategy for a group of connected and autonomous hybrid electric vehicles (HEVs) with the purpose of optimising fuel economy while guaranteeing traffic mobility and vehicle safety. In the hierarchical control architecture, a decentralised stochastic model predictive control (SMPC)‐based higher level controller incorporating signal phase and timing information is formulated to optimise the velocity profile of each vehicle, and an adaptive equivalent consumption minimisation strategy based lower level controller is employed for the energy management control of the HEVs. Creatively, random errors of the control variable are considered in the SMPC framework. The errors are discretised and modelled as a Markov process and the state transition matrix of the errors is generated randomly to capture the error transition dynamics. To solve the SMPC problem more efficiently, a scenario‐based SMPC is employed. Moreover, the propulsion and recuperation efficiencies of the lower level controller are calculated at each time step with measurable variables, and fed back to the higher level controller for velocity optimisation in next time step. Simulation results validate the control effectiveness and advantages of the proposed control architecture.

Qiu, Shaolin↗

Binding energetics of substitutional and interstitial helium and di-helium defects with grain boundary structure in α-Fe

The formation/binding energetics and length scales associated with the interaction between He atoms and grain boundaries in BCC α-Fe were explored. Ten different low Σ grain boundaries from the 〈100〉 and 〈110〉 symmetric tilt grain boundary systems were used. In this work, we then calculated formation/binding energies for 1–2 He atoms in the substitutional and interstitial sites (HeV, He{sub 2}V, HeInt, He{sub 2}Int) at all potential grain boundary sites within 15 Å of the boundary (52 826 simulations total). The present results provide detailed information about the interaction energies and length scales of 1–2 He atoms with grain boundaries for the structures examined. A number of interesting new findings emerge from the present study. For instance, the Σ3(112) twin boundary in BCC Fe possesses a much smaller binding energy than other boundaries, which corresponds in long time dynamics simulations to the ability of an interstitial He defect to break away from the boundary in simulations on the order of nanoseconds. Additionally, positive correlations between the calculated formation/binding energies of the He defects (R > 0.9) asserts that the local environment surrounding each site strongly influences the He defect energies and that highly accurate quantum mechanics calculations of lower order defects may be an adequate predictor of higher order defects. Various metrics to quantify or classify the local environment were compared with the He defect binding energies. The present work shows that the binding and formation energies for He defects are important for understanding the physics of He diffusion and trapping by grain boundaries, which can be important for modeling He interactions in polycrystalline steels.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Structural and functional analyses reveal promiscuous and species specific use of ephrin receptors by Cedar virus

Cedar virus (CedV) is a bat-borne henipavirus related to Nipah virus (NiV) and Hendra virus (HeV), zoonotic agents of fatal human disease. CedV receptor-binding protein (G) shares only ~30% sequence identity with those of NiV and HeV, although they can all use ephrin-B2 as an entry receptor. We demonstrate that CedV also enters cells through additional B- and A-class ephrins (ephrin-B1, ephrin-A2, and ephrin-A5) and report the crystal structure of the CedV G ectodomain alone and in complex with ephrin-B1 or ephrin-B2. The CedV G receptor-binding site is structurally distinct from other henipaviruses, underlying its capability to accommodate additional ephrin receptors. We also show that CedV can enter cells through mouse ephrin-A1 but not human ephrin-A1, which differ by 1 residue in the key contact region. This is evidence of species specific ephrin receptor usage by a henipavirus, and implicates additional ephrin receptors in potential zoonotic transmission.

59 BASIC BIOLOGICAL SCIENCES↗