*1.3. TCO of EVs*

Most ownership and total cost of ownership (TCO) studies of BEV and hybrids are relatively recent, due to the emergence of the relevant technology [7]. One study developed a model of the performance, energy use, manufacturing cost, retail cost, and lifecycle cost of BEVs versus comparable gasoline-powered vehicles [13]. This study found that BEVs were cost-competitive, but the battery life and manufacturing costs were concerns. In another study, a vehicle cost simulation was used to analyze the manufacturing costs, retail prices, and lifecycle costs of hybrid gasoline-electric vehicles, conventional vehicles, electric-drive vehicles, and other alternative-fuel vehicles [14]. However, the research is dated. This study uses methods like the previous studies but updates the analysis with newer data in a publicly available format. Another study indicated that hybrid vehicles were better than gas-powered vehicles in terms of life-cycle costs and high travel miles [15]. Palmer et al. used panel regression to compare life-cycle costs for four geographic location. The authors did not forecast energy costs or consider seasonality. The vehicle data were also dated [16].

One study focused on the battery performance impact on TCO. This study found that TCO for EVs and PHEVs was 24 to 36% higher than HEVs [17]. Another study found that HEVs were associated with lower TCO in comparison with other EVs [18]. The purchase of hybrids is correlated with their TCO, and cost parity is reached relatively quickly (e.g., 16 months in the United Kingdom) [16]. Further, consumers prefer PHEVs to HEVs, with only a few percent opting for pure EVs [19].

A 2018 study demonstrated that, with proper policy incentives, TCO was better for EVs than than HEVs [20]. This study suggests that even without subsidies, EVs will gain market share by 2025 [20]. EVs are cost competitive without incentives now. However, incentives for purchase should be tailored based on battery development [21,22]. Further, grid-powered EVs (and PHEVs) may have deleterious effects on the grid [23,24] and produce unwanted pollution due to the reliance on grid power [25]. A solution for handling this problem is the use of solar charging for EVs [26]. Such a solution has been used in both industry [26] and in residences [27]. Fulton [28] compared specific BEV and non-plugin hybrids via simulation estimating that both were reasonable options. None of these studies provided a publicly available simulation with flexible parameters that compared break-even costs for gasoline vehicles, BEV, and non-plug hybrid vehicles.

Another, somewhat dated German study comparing ownership cost of BEV versus gas vehicles concluded a break-even cost of six years with 4 kW vehicles [29]. However, studies all depend on geography and climate assessments, as BEVs and HEVs experience different decay rates for the lithium ion batteries, based on climatology and driving experience [30]. Based on this discussion, the evidence for BEVs versus PHEVs is mixed. What motivates consumers to buy either is another concern altogether.

## *1.4. Consumer Decision Making in Vehicle Purchasing*

Marketing studies have investigated consumer preferences and BEV viability [31]. Shin et al. evaluated how consumers would change habits based on the adoption of a BEV and how heterogeneity of vehicles might affect the market [32]. He, Chen and Conzelmann evaluated vehicle usage and consumer profile attributes, in order to assess vehicle usage versus consumer choices of hybrid vehicles [33]. Another study indicated how utility prices versus replacement costs are factors in consumer decision making [34]. All these studies provide evidence that given proper capabilities and price, EVs may be acceptable to consumers.

### *1.5. Modeling Considerations*

From their unique perspective, Ozdemir and Hartmann estimated the optimal electric driving range for different oil price levels [35]. Some researchers have helped refine calculation of fuel consumption and emission factors based on driving styles [36]. This type of work provides a good framework for cost estimation. Focusing on driving range and gasoline costs, one study compared the lifecycle costs of electric cars to similar gasoline-powered vehicles [37]. In their study, the authors concluded that electric cars with 150 km range are viable and meet most consumer needs. The effects of charging behaviors (i.e., time of day and location) on electricity demand was studied by Weiller [38]. The study estimated a consumption of 1.5–2.0 kWh per day with home electric chargers. These studies provide the framework for simulation analysis.

## *1.6. Study Research Question and Significance*

This study provides a user-interactive simulation to estimate the consumer costs and environmental costs for various vehicle configurations. The research question for this study is straightforward: What consumer trade-off considerations make purchasing a BEV/HEV versus a gasoline-powered vehicle reasonable in terms of acquisition costs, operations and maintenance costs, disposal/residual costs, and environmental costs? The study addresses these questions through a freely available and online simulation located here: https://rminator.shinyapps.io/Vehicles/. This simulation that compares two vehicle options simultaneously.

Unlike much of the other work in this field, this study does not focus on a particular vehicle or vehicle set. Instead, the focus is on a capability set that is customizable based on current and emerging technology (e.g., the improvement of miles per kWh in emerging vehicle lines). This differentiates the work from other simulations which are based on fixed capability values.

This study appears to be the first to provide a publicly available simulation accessible by any interested party that compares two purchase options simultaneously. It is likely the first paper to simulate the effects of solar recharging of EV vehicles on both cost-benefit for the consumer and environmental benefit (e.g., CO2, NOx + NMOG, PM, and HCHO) simultaneously, demonstrating how solar-based charging of electrical vehicles reduces CO2 emissions (as an example). No other study appears to estimate acquisition costs for solar panels necessary to support a residential EV that is to be charged by such means. This work appears to provide the only user-available sensitivity analysis for various options of natural gas, electricity, or solar residential power options coupled with solar power generation capability estimates that vary by state and Error, Trend, and Seasonality (ETS) forecasts of utility costs based on Energy Information Administration data. The study is novel in that it combines user-based input with time series forecasting and simulation to generate interesting TCO and environmental assessments. The study also addresses the primary theme of the journal's special issue: Energy savings and reduced environmental impact associated with solar versus natural gas versus coal-powered grid systems.
