An Optimization Model for Plug-In Hybrid Electric Vehicles

Widespread use of alternative hybrid powertrains currently appears inevitable and many opportunities for substantial progress remain. The necessity for environmentally friendly vehicles, in conjunction with increasing concerns regarding U.S. dependency on foreign oil and climate change, has led to significant investment in enhancing the propulsion portfolio with new technologies. Recently, plug-in hybrid electric vehicles (PHEVs) have attracted considerable attention due to their potential to reduce petroleum consumption and greenhouse gas (GHG) emissions in the transportation sector. PHEVs are especially appealing for short daily commutes with excessive stop-and-go driving. However, the high costs associated with their components, and in particular, with their energy storage systems have been significant barriers to extensive market penetration of PHEVs. In the research reported here, we investigated the implications of motor/generator and battery size on fuel economy and GHG emissions in a medium duty PHEV. An optimization framework is proposed and applied to two different parallel powertrain configurations, pretransmission and post transmission, to derive the Pareto frontier with respect to motor/generator and battery size. The optimization and modeling approach adopted here facilitates better understanding of the potential benefits from proper selection of motor/generator and battery size on fuel economy and GHG emissions. This understanding can help us identify the appropriate sizing of these components and thus reducing the PHEV cost. Addressing optimal sizing of PHEV components could aim at an extensive market penetration of PHEVs.

Electrified vehicles, including plug-in hybrid electric vehicles (PHEVs) and battery electric vehicles (BEVs), have the potential to reduce greenhouse gas (GHG) emissions from personal transportation by shifting energy demand from gasoline to electricity. GHG reduction potential depends on vehicle design, adoption, driving and charging patterns, charging infrastructure, and electricity generation mix. We construct an optimization model to study these factors by determining optimal design of conventional vehicles (CVs), hybrid electric vehicles (HEVs), PHEVs, and BEVs and optimal allocation of vehicle designs and charging infrastructure in the fleet for minimum lifecycle GHG emissions over a range of scenarios. We focus on vehicles with similar size and acceleration to a Toyota Prius under urban EPA driving conditions. We find that under today’s U.S. average grid mix, the vehicle fleet allocated for minimum GHG emissions includes HEVs and PHEVs with ~30 miles (48 km) of electric range. Allocating only CVs, HEVs, PHEVs, or BEVs will produce 86%, 1%, 0%, or 13+% more life cycle GHG emissions, respectively. Unlike BEVs, PHEVs do consume some gasoline; however, PHEVs can power a large portion of vehicle miles on electrical energy while accommodating infrequent long trips without need for a large battery pack, with its corresponding production and weight implications. Availability of workplace charging for 90% of vehicles optimistically reduces optimized GHG emissions by 0.5%. Under decarbonized grid scenarios, larger battery packs are more competitive and reduce life cycle GHG emissions significantly. Future work will relax modeling assumptions and address life cycle cost and cost-effectiveness of GHG reductions.

Researchers at Argonne National Laboratory expanded the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model and incorporated the fuel economy and electricity use of alternative fuel/vehicle systems simulated by the Powertrain System Analysis Toolkit (PSAT) to conduct a well-to-wheels (WTW) analysis of energy use and greenhouse gas (GHG) emissions of plug-in hybrid electric vehicles (PHEVs). The WTW results were separately calculated for the blended charge-depleting (CD) and charge-sustaining (CS) modes of PHEV operation and then combined by using a weighting factor that represented the CD vehicle-miles-traveled (VMT) share. As indicated by PSAT simulations of the CD operation, grid electricity accounted for a share of the vehicle's total energy use, ranging from 6% for a PHEV 10 to 24% for a PHEV 40, based on CD VMT shares of 23% and 63%, respectively. In addition to the PHEV's fuel economy and type of on-board fuel, the marginal electricity generation mix used to charge the vehicle impacted the WTW results, especially GHG emissions. Three North American Electric Reliability Corporation regions (4, 6, and 13) were selected for this analysis, because they encompassed large metropolitan areas (Illinois, New York, and California, respectively) and provided a significant variation of marginal generation mixes. The WTW results were also reported for the U.S. generation mix and renewable electricity to examine cases of average and clean mixes, respectively. For an all-electric range (AER) between 10 mi and 40 mi, PHEVs that employed petroleum fuels (gasoline and diesel), a blend of 85% ethanol and 15% gasoline (E85), and hydrogen were shown to offer a 40-60%, 70-90%, and more than 90% reduction in petroleum energy use and a 30-60%, 40-80%, and 10-100% reduction in GHG emissions, respectively, relative to an internal combustion engine vehicle that used gasoline. The spread of WTW GHG emissions among the different fuel production technologies and grid generation mixes was wider than the spread of petroleum energy use, mainly due to the diverse fuel production technologies and feedstock sources for the fuels considered in this analysis. The PHEVs offered reductions in petroleum energy use as compared with regular hybrid electric vehicles (HEVs). More petroleum energy savings were realized as the AER increased, except when the marginal grid mix was dominated by oil-fired power generation. Similarly, more GHG emissions reductions were realized at higher AERs, except when the marginal grid generation mix was dominated by oil or coal. Electricity from renewable sources realized the largest reductions in petroleum energy use and GHG emissions for all PHEVs as the AER increased. The PHEVs that employ biomass-based fuels (e.g., biomass-E85 and -hydrogen) may not realize GHG emissions benefits over regular HEVs if the marginal generation mix is dominated by fossil sources. Uncertainties are associated with the adopted PHEV fuel consumption and marginal generation mix simulation results, which impact the WTW results and require further research. More disaggregate marginal generation data within control areas (where the actual dispatching occurs) and an improved dispatch modeling are needed to accurately assess the impact of PHEV electrification. The market penetration of the PHEVs, their total electric load, and their role as complements rather than replacements of regular HEVs are also uncertain. The effects of the number of daily charges, the time of charging, and the charging capacity have not been evaluated in this study. A more robust analysis of the VMT share of the CD operation is also needed.

Plug-in hybrid electric vehicles (PHEVs) have potential to reduce greenhouse gas (GHG) emissions in the U.S. light-duty vehicle fleet. GHG emissions from PHEVs and other vehicles depend on both vehicle design and driver behavior. We pose a twice-differentiable, factorable mixed-integer nonlinear programming model utilizing vehicle physics simulation, battery degradation data, and U.S. driving data to determine optimal vehicle design and allocation for minimizing lifecycle greenhouse gas (GHG) emissions. The resulting nonconvex optimization problem is solved using a convexification-based branch-and-reduce algorithm, which achieves global solutions. In contrast, a randomized multistart approach with local search algorithms finds global solutions in 59% of trials for the two-vehicle case and 18% of trials for the three-vehicle case. Results indicate that minimum GHG emissions is achieved with a mix of PHEVs sized for around 35 miles of electric travel. Larger battery packs allow longer travel on electric power, but additional battery production and weight result in higher GHG emissions, unless significant grid decarbonization is achieved. PHEVs offer a nearly 50% reduction in life cycle GHG emissions relative to equivalent conventional vehicles and about 5% improvement over ordinary hybrid electric vehicles. Optimal allocation of different vehicles to different drivers turns out to be of second order importance for minimizing net life cycle GHGs.

Impact of battery weight and charging patterns on the economic and environmental benefits of plug-in hybrid vehicles

Plug-in hybrid electric vehicles (PHEVs) have the potential to reduce green house gases emissions and provide a promising alternative to conventional internal combustion engine vehicles. However, PHEVs have not been widely adopted in comparison to the conventional vehicles due to their high costs and short charging intervals. Since PHEVs rely on large storage batteries relative to the conventional vehicles, the characteristics and design issues associated with PHEV batteries play an important role in the potential adoption of PHEVs. Consumer acceptance and adoption of PHEVs mainly depends on fuel economy, operating cost, operation green house gas (GHG) emissions, power and performance, and safety among other characteristics. We compare the operational performance of PHEV20 (PHEV version sized for 20 miles of all electric range) based on fuel economy, operating cost, and greenhouse gas (GHG) emissions through Pareto set point identification approach for 15 different types of batteries, including lithium-ion, nickel metal hydride (NiMH), nickel zinc (NiZn), and lead acid batteries. It is found that two from 15 batteries dominate the rest. Among the two, a NiMH (type ess_nimh_90_72_ovonic) gives the highest fuel economy, and a lithium-ion (type ess_li_7_303) yields the lowest operating cost and GHG emissions. From comparing nine batteries that are either on or close to the Pareto frontier, one can see that lithium-ion and NiMH batteries offer better fuel economy than lead-acid batteries. Though lithium-ion batteries bear clear advantage on operating costs and GHG emissions, NiMH and lead-acid batteries show similar performances from these two aspects.

Plug-in hybrid electric vehicle (PHEVs) technology has the potential to address economic, environmental, and national security concerns in the United States by reducing operating cost, greenhouse gas (GHG) emissions and petroleum consumption. However, the net implications of PHEVs depend critically on the distances they are driven between charges: Urban drivers with short commutes who can charge frequently may benefit economically from PHEVs while also reducing fuel consumption and GHG emissions, but drivers who cannot charge frequently are unlikely to make up the cost of large PHEV battery packs with future fuel cost savings. We construct an optimization model to determine the optimal PHEV design and optimal allocation of PHEVs, hybrid-electric vehicles (HEVs) and conventional vehicles (CVs) to drivers in order to minimize net cost, fuel consumption, and GHG emissions. We use data from the 2001 National Household Transportation Survey to estimate the distribution of distance driven per day across vehicles. We find that (1) minimum fuel consumption is achieved by assigning large capacity PHEVs to all drivers; (2) minimum cost is achieved by assigning small capacity PHEVs to all drivers; and (3) minimum greenhouse gas emissions is achieved by assigning medium-capacity PHEVs to drivers who can charge frequently and large-capacity PHEVs to drivers who charge less frequently.

Plug-in hybrid electric vehicle (PHEV) technology has the potential to reduce operating cost, greenhouse gas (GHG) emissions, and petroleum consumption in the transportation sector. However, the net effects of PHEVs depend critically on vehicle design, battery technology, and charging frequency. To examine these implications, we develop an optimization model integrating vehicle physics simulation, battery degradation data, and U.S. driving data. The model identifies optimal vehicle designs and allocation of vehicles to drivers for minimum net life cycle cost, GHG emissions, and petroleum consumption under a range of scenarios. We compare conventional and hybrid electric vehicles (HEVs) to PHEVs with equivalent size and performance (similar to a Toyota Prius) under urban driving conditions. We find that while PHEVs with large battery packs minimize petroleum consumption, a mix of PHEVs with packs sized for ∼25–50 miles of electric travel under the average U.S. grid mix (or ∼35–60 miles under decarbonized grid scenarios) produces the greatest reduction in life cycle GHG emissions. Life cycle cost and GHG emissions are minimized using high battery swing and replacing batteries as needed, rather than designing underutilized capacity into the vehicle with corresponding production, weight, and cost implications. At 2008 average U.S. energy prices, Li-ion battery pack costs must fall below $590/kW h at a 5% discount rate or below $410/kW h at a 10% rate for PHEVs to be cost competitive with HEVs. Carbon allowance prices offer little leverage for improving cost competitiveness of PHEVs. PHEV life cycle costs must fall to within a few percent of HEVs in order to offer a cost-effective approach to GHG reduction.

Plug-in hybrid electric vehicle (PHEV) technology has the potential to help address economic, environmental, and national security concerns in the United States by reducing operating cost, greenhouse gas (GHG) emissions and petroleum consumption from the transportation sector. However, the net effects of PHEVs depend critically on vehicle design, battery technology, and charging frequency. To examine these implications, we develop an integrated optimization model utilizing vehicle physics simulation, battery degradation data, and U.S. driving data to determine optimal vehicle design and allocation of vehicles to drivers for minimum life cycle cost, GHG emissions, and petroleum consumption. We find that, while PHEVs with large battery capacity minimize petroleum consumption, a mix of PHEVs sized for 25–40 miles of electric travel produces the greatest reduction in lifecycle GHG emissions. At today’s average US energy prices, battery pack cost must fall below $460/kWh (below $300/kWh for a 10% discount rate) for PHEVs to be cost competitive with ordinary hybrid electric vehicles (HEVs). Carbon allowance prices have marginal impact on optimal design or allocation of PHEVs even at $100/tonne. We find that the maximum battery swing should be utilized to achieve minimum life cycle cost, GHGs, and petroleum consumption. Increased swing enables greater all-electric range (AER) to be achieved with smaller battery packs, improving cost competitiveness of PHEVs. Hence, existing policies that subsidize battery cost for PHEVs would likely be better tied to AER, rather than total battery capacity.

Technological progress and industrial activities have affected air quality and increased greenhouse gas (GHG) emissions. GHGs are emitted from several sources, such as refineries, power plants and vehicles. The transportation sector contributes significantly to GHG emissions, primarily via vehicles powered by petroleum-based fuels and dispersed throughout residential territories. Plug-in hybrid electrical vehicles (PHEVs), which displace some portion of the petroleum with electricity, play a key role in reducing emissions. However, when power plants generate more electricity, they also produce more pollution. Therefore, utilizing PHEVs does not always guarantee a reduction in GHG emissions. This paper, which focuses on introducing and categorizing GHGs, explores the factors and conditions that make the impact of PHEVs on emissions complex and challenging. This paper also introduces various optimum charging strategies with different objectives. The paper's main objective is to examine the fluctuation of GHGs in response to these strategies. The result of this study depicts the behaviors of the different components of GHGs under different charging strategies.

Multiobjective component sizing of a hybrid ethanol-electric vehicle propulsion system

Plug-in hybrid electric vehicles (PHEVs), which use electricity from the grid to power a portion of travel, could play a role in reducing greenhouse gas (GHG) emissions from the transport sector. However, meaningful GHG emissions reductions with PHEVs are conditional on low-carbon electricity sources. We assess life cycle GHG emissions from PHEVs and find that they reduce GHG emissions by 32% compared to conventional vehicles, but have small reductions compared to traditional hybrids. Batteries are an important component of PHEVs, and GHGs associated with lithium-ion battery materials and production account for 2-5% of life cycle emissions from PHEVs. We consider cellulosic ethanol use and various carbon intensities of electricity. The reduced liquid fuel requirements of PHEVs could leverage limited cellulosic ethanol resources. Electricity generation infrastructure is long-lived, and technology decisions within the next decade about electricity supplies in the power sector will affectthe potential for large GHG emissions reductions with PHEVs for several decades.

A population of drivers was simulated using a microsimulation model. Consistent with the 2001 National Household Travel Survey (NHTS), a wide range of daily driving distance was observed. This heterogeneity implies that some drivers will realize greater fuel savings from driving a plug-in hybrid electric vehicle (PHEV) than others, therefore, consumers who choose to purchase PHEVs may tend to be those who drive farther than average. The model was used to examine the effects of this difference in driving by estimating fuel use, electricity demand and GHG emissions by two populations, one assigned PHEVs at random to some fraction of drivers, and the other assigned PHEVs to drivers who realized operating cost savings at least as great as the amortized incremental cost of the PHEV relative to a comparable conventional vehicle. These two populations showed different distributions of daily driving distance, with the population of PHEV drivers selected on the basis of operating cost savings driving 40% farther per day on average than average drivers. This difference indicates the possible range of driving patterns of future PHEV drivers, which should be taken into account when estimating fuel savings and GHG reductions from PHEVs. For example, if 20% of U.S. vehicles were PHEVs, we find a potential reduction of fuel use of 0.17 gal per day per vehicle if PHEVs substitute randomly for conventional vehicles, whereas the fuel savings is as large as 0.26 gal per day per vehicle if PHEVs are substituted according to operating cost savings. Similar differences in GHG emissions were estimated as well. The effects of electricity demand management on charging PHEVs was examined for these two populations. It was found for both that only a small fraction of PHEVs were impacted by interruptible electricity service (no charging permitted during peak hours). Most PHEV drivers were able to charge sufficiently during off-peak hours and saw little change in operating costs. This implies that interruptible electricity service may impact operating costs of only a small fraction of PHEV drivers.

Major US electric utility climate pledges have the potential to collectively reduce power sector emissions by one-third

Plug-in hybrid electric vehicle (PHEV) technology is receiving attention as an approach to reducing U.S. dependency on foreign oil and emissions of greenhouse gases (GHG) from the transportation sector. Because plug-in vehicles require large batteries for energy storage, battery weight can have a significant impact on vehicle performance: Additional storage capacity increases the range that a PHEV can travel on electricity from the grid; however, the associated increased weight causes reduced efficiency in transforming electricity and gasoline into miles driven. We examine vehicle simulation models for PHEVs and identify trends in fuel consumption, operating costs, and GHG emissions as battery capacity is increased. We find that PHEVs with large battery capacity consume less gasoline than small capacity PHEVs when charged every 200 miles or less. When charged frequently, small capacity PHEVs are less expensive to operate and release fewer GHGs, but medium and large capacity PHEVs are more efficient for drivers that charge every 25–100 miles. While statistics on average commute length suggest that frequent charges are possible, answering the question of which PHEV designs will best help to achieve national goals will require a realistic understanding of likely consumer driving and charging behavior as well as future trends in electricity generation.