Predicting the Potential Market for Electric Vehicles

Forecasting the potential demand for electric vehicles is a challenging task. Because most studies for new technologies rely on stated preference (SP) data, market share predictions will reflect shares in the SP data and not in the real market. Moreover, typical disaggregate demand models are suitable to forecast demand in relatively stable markets, but show limitations in the case of innovations. When predicting the market for new products it is crucial to account for the role played by innovation and how it penetrates the new market over time through a diffusion process. However, typical diffusion models in marketing research use fairly simple demand models. In this paper we discuss the problem of predicting market shares for new products and suggest a method that combines advanced choice models with a diffusion model to take into account that new products often need time to gain a significant market share. We have the advantage of a relatively unique databank where respondents were submitted to the same stated choice experiment before and after experiencing an electric vehicle. Results show that typical choice models forecast a demand that is too restrictive in the long period. Accounting for the diffusion effect, instead allows predicting the usual slow penetration of a new product in the initial years after product launch and a faster market share increase after diffusion takes place. </jats:p

Enabling Quality-oriented Process Development for sulfidic All-Solid-State Battery Cathodes

After major advances in material research throughout recent years, the industrialization of all-solid-state batteries now depends on the development of cost-effective production technology for novel materials and components. To enable a fast production scale-up and complex process interdependency handling, production engineering needs a quantitative evaluation and comparison approach for manufacturing strategies and process parameter settings. To address this challenge, we derive microstructural quality criteria from specifications at the product-level such as driving range and charging speed of battery electric vehicles. These range from porosity and agglomerate density on a macroscopic level to microscopic properties such as pore size distribution and particle contacts. By listing comprehensive characterization methods, the work enables engineers to efficiently evaluate these criteria. Experimentally applying the proposed approach, the influence of different mixing process parameters is analyzed. Thereby, sulfidic composite cathodes manufactured in a scalable procedure are used as samples

Electric Car Purchase Price as a Factor Determining Consumers’ Choice and their Views on Incentives in Europe

The deployment of zero-emission vehicles has the potential to drastically reduce air pollution and greenhouse gas emissions from road transport. The purpose of this study is to provide evidence on, and quantify the factors that influence, the European market for electric and fuel cell car technologies. The paper reports the results of a stated preference survey among 1,248 car owners in France, Germany, Italy, Poland, Spain and the United Kingdom. The variables that influence powertrain choice are quantified in a nested multinomial logit model. We find that the electric car purchase price continues to be a major deterrent to sales in the surveyed countries. The majority of the respondents considered government incentives as fundamental or important for considering an electric car purchase. Because of the differences in the socio-economic characteristics of consumers in each country, the effectiveness of government incentives may vary across Europe

A Simplified Approach to Estimate EV Charging Demand in Urban Area: An Italian Case Study

The development and the diffusion of the electromobility is crucial for reducing air pollution and increase sustainable transport. In particular, electrification of private mobility has a significantly role in the energy transition within urban areas, since the progressive substitution of conventional passenger cars by electric vehicles (EVs) leads to the decarbonisation of transport sector without direct emissions. However, increasing EV penetration in the market forces an expansion of the existing charging infrastructure with potential negative impacts on the distribution grid. In this context, a simplified approach is proposed to estimate the energy and power demand owing to the recharge of electric passenger cars within the city of Turin in Italy. This novel approach is based on the usage of floating car data (FCD) to identify the travel behaviour and parking habits of a non-EV passenger car in the city. Mobility data were then used to evaluate EVs energy consumption and charging needs considering different charging options (public or domestic) and range anxiety in different scenarios of EV diffusion. Aggregated load profiles and demand were finally evaluated both for the whole and for each zone of the city as possible resource for city planner or distribution system operators (DSO)

Simulating Electric Vehicle Diffusion and Charging Activities in France and Germany

Plug-in electric vehicles (PEV) are considered to reduce oil dependency, noise, and local air pollution as well as greenhouse gas emissions caused by road transportation. Today, the early market penetration phase has started and can be observed in many countries. But how could the diffusion and adoption of PEV be modeled to create consistent scenarios? With which PEV driving and charging behavior can these scenarios be associated and what load-shifting potentials can be derived? This work provides an answer to these questions by describing a hybrid modeling approach of a PEV diffusion scenario consisting of a top-down macro-econometric Bass model, answering the question as to at what point in time how many PEV will be on the market, and a bottom-up micro-econometric binary logistic PEV adoption model answering who is likely to adopt. This set of methods is applied to representative mobility data sets available for France and Germany in order to simulate driving and charging behaviors of potential French and German PEV adopters. In addition, a sampling method is presented, which reduces computational times while intending to remain representative of the population of PEV adopters considered. This approach enables the consideration of PEV at a detailed level in an agent-based energy system model focusing on European day-ahead markets. Results show that PEV diffusion dynamics are slightly higher in France than in Germany. Furthermore, average plug-in times, average active charging periods, average load-shifting potentials, and average energy charged per PEV differ slightly between France and Germany. Computational times can be reduced by our approach, resulting in the ability to better integrate PEV diffusion, adoption, and representative charging demand in bottom-up energy system models that simulate European wholesale electricity markets

Simulating the market penetration of cars with alternative fuelpowertrain technologies in Italy

This paper evaluates the market penetration of cars with alternative fuelpowertrain technologies in Italy under various scenarios. Seven cars on sale in 2013 are considered: the Ford Fiesta (diesel), the VW Polo (gasoline), the Fiat Punto Evo (bi-fuel \u2013 CNG), the Natural Power Alfa Romeo Mito (bi-fuel \u2013 LPG), the Toyota Yaris (hybrid \u2013 gasoline), the Peugeot iOn (BEV \u2013 owned battery), the Renault Zoe (BEV \u2013 leased battery). A Mixed Error Component Logit model is estimated based on data collected via a stated preference choice survey administered in 2013 in various Italian cities. The model's parameters are then used to build a Monte Carlo simulation model which allows evaluating, under different scenarios, the market penetration of the seven cars. The main findings are that (a) the subsidies enacted by the Italian government in favour of the low CO2 emitting cars appear to favour mostly the Ford Fiesta (diesel); (b) a three-fold increase in the BEVs range would not change their market share significantly (about 2%); and (c) only a combination of changes such as the introduction of a subsidy equal to \u20ac5000, the decrease of the purchase price for BEVs by \u20ac5000, the increase in the battery range, and the increase in the conventional fuel price would significantly increase the BEVs' market share, raising it to about 15%