3.1. Analysis of Factors Promoting the Growth of Electric Vehicles
At present, the main factors affecting the development of electric vehicles include the factors of the electric vehicle industry itself and other factors related to electric vehicles.
For the electric vehicle industry itself, the main influencing factors are the technical development level of the electric vehicle industry, such as the level of electric vehicle charging infrastructure construction and the progress level of battery technology, which includes battery range, fast and slow charging time [
25,
26], and adaptability to low temperature in winter, etc. [
27].
From the point of developing the low temperature adaptability of the electric vehicle in winter, through attaching with the power battery manufacturers, such as BYD (Shenzhen, China), CATL (Ningde, China), collecting the official electric vehicle test report in cold weather (Mohe in Heilongjiang, Zhangjiakou in Hebei), and making electric vehicle owners using condition research in the north of Xinjiang, it is found that foreign electric vehicle range about 20~25% lower in winter (Tesla 20% lower), domestic electric vehicle range about 40~50% lower in winter. The daily mileage of electric vehicles is about 150 km, and electric vehicles usually have 30 to 40% of base power in winter, charging power is 4~6 kw. during the trough period, it can be charged to more than 80% in 7~9 h (including preheating time) to meet the daily driving needs. With the iterative progress of technology, the battery safety, charging time and capacity are constantly improving, and with the improvement of the battery management system (BMS) and auxiliary heating system, the problem of the decline of electric vehicle’s winter rangeability is being solved.
At the same time, in the early stage of the development of the electric vehicle industry, the promotion of electric vehicles is affected by the strength of policy support and media advertising. Policy support is determined by power grid support strength and government support strength. If the number of days of severe weather pollution increases in a year, CO2 emissions from fuel vehicles increased rapidly, the government will actively promote the development of electric vehicles, such as implementing incentive price or subsidy policies and encouraging the research and development of new technologies. If the proportion of electric vehicles discharging into the grid increases with the increase of the number of electric vehicles, the power grid can realize the benefit of peak clipping and valley filling, and the grid will also increase its support for the development of electric vehicles. The interaction between electric vehicles and the power grid depends on charging piles, so the support of the power grid for the development of electric vehicles is mainly reflected in the construction of charging piles.
The main factor related to electric vehicles is the increase in oil price, which increases the cost of using traditional fuel vehicles, thus promoting the promotion of electric vehicles. The purchase intention of electric vehicle users is affected by factors such as electric vehicle economy, charging convenience, and electric vehicle subsidy level. The pile-to-vehicle ratio refers to the ratio between electric vehicle charging and changing facilities and the number of electric vehicles in a certain area. The larger the ratio is, the greater the proportion of electric vehicle charging and changing facilities in the number of electric vehicles, and the greater the charging convenience of electric vehicle users will be.
3.2. Improved Bass Modeling
Bass model, also known as the Bass diffusion model, was created by American marketing scholar Frank Bass. It is a market share prediction model specifically for the adoption and diffusion of innovative products and technologies. Innovative adopters. Another group of potential adopters, whose time to adopt a new product is influenced by other members of society, and their pressure increases as the number of early adopters increases. Bass calls these potential adopters imitators [
28,
29].
where
f(
t + 1) is the proportion of the number of new consumers in
t + 1 year to the total potential consumers in
t + 1 year.
F(
t) refers to the proportion of the number of new products in the cumulative total of similar products used in the market in that year.
p is the innovation coefficient (external influence coefficient), which reflects the number of consumers who will purchase new products under external influence.
q is the imitation coefficient (internal influence coefficient), which reflects the number of consumers affected by network effects and others’ purchasing decisions.
The Bass model expresses the nature of the diffusion process with mathematical equations, which greatly simplifies people’s understanding of innovation diffusion and makes it systematic. As a new technology product, the maximum market potential of electric vehicles depends on the product technology maturity, coverage of public supporting facilities, government media publicity and subsidies.
Parameters
p and
q determine the shape of curve
F(
t) in the Bass model, and the values of
p and
q are mostly determined by fitting historical data of market share in relevant studies. However, electric private cars are still in the early stage of promotion, and the historical data such as sales volume and per capita ownership are not perfect. The method to determine the parameters based on data fitting is not available at present [
30]. Therefore, this paper builds an improved Bass model on the basis of literature [
31], changes the constant coefficients p and q estimated based on historical conditions into the modeling of parameters p and q under the consideration of relevant factors affecting the growth of electric vehicles, and introduces the price correction coefficient. The iterative model of the electric vehicle ownership prediction matrix is shown as follows:
where
E(
t) is the ownership of private electric vehicles in the
t year.
V(
t) is the total number of private vehicles in the
t year. λ is the annual natural growth rate of private vehicles.
F(
t + 1) is the proportion of the number of new electric vehicles in
t + 1 year to the total potential vehicles sold in the market in
t + 1 year.
F(
t) is the penetration rate of private electric vehicles in the
t year, and is the proportion of the ownership of private electric vehicles in the
t year to the total number of private vehicles in the
t year, with a value range of [0, 1].
F(
t + 1) is the proportion of the number of new electric vehicles in
t + 1 year to the total potential vehicles sold in the market in
t + 1 year.
p(
t) is the innovation coefficient.
q(
t) is the imitation coefficient.
x(
t) is the price correction coefficient.
The innovation coefficient
p(
t) is affected by policy intensity, media publicity effect and technology maturity. This part of users are consumers who spontaneously adopt electric vehicles, and are not affected by users who have already purchased electric vehicles. They are called innovative adopters. Considering that there is a lag between the media publicity and the crowd recognition of a new idea or product, the increase in the acceptance of electric vehicles by the crowd is related to the policy media publicity and the technical maturity of electric vehicles, and the innovation coefficient
p(
t) is expressed as follows:
where
p(
t) represents the innovation coefficient in the
t year;
M represents the propaganda intensity of policies and media, and its value range is [0, 1].
T(
t) is the technical maturity of electric vehicles in the
t year, such as the development of electric vehicle batteries and related charging infrastructure. α is the technical update coefficient. The innovation coefficient
p(
t) defined in the above equation is a time-varying parameter, which can reflect the dynamic change of the number of consumers who spontaneously adopt new products.
Imitation coefficient
q(
t) is affected by electric vehicle visibility and user satisfaction. This part of users are consumers who are influenced by the users who previously purchased electric vehicles, called imitators. The imitation coefficient is related to the occurrence frequency of electric vehicles in daily life and the evaluation of electric vehicles by electric vehicle owners around potential consumers. The imitation coefficient
q(
t) is expressed as follows:
where the
q0 is the imitation coefficient under the condition of complete satisfaction of the owners of private electric vehicles, which can be calculated by referring to the upper limit of the imitation coefficient of other durable goods.
c(
t) is the relative visibility of private electric vehicles in the city. Relative visibility can be expressed by the permeability of private electric vehicles
F(
t), that is,
c(
t) =
F(
t).
s(
t) is the overall satisfaction of private electric vehicle owners in this city, represented by the charging convenience index, that is, the convenience of charging after the completion of the daily driving task, with a value range of [0, 1].
where
is the average daily mileage.
L is the range of electric vehicles.
rt is the pile-to-vehicle ratio.
is the regulator.
The price correction coefficient
x(
t) is affected by price cost and policy subsidies, and there is a competitive relationship between electric vehicles and conventional fuel vehicles. Considering the purchase and use costs of electric vehicles relative to conventional energy vehicles, the price correction coefficient
x(
t) is expressed as follows:
Among them, the CEV(t) and CCV(t) is the total cost of electric vehicles and conventional fuel vehicles respectively, and is the present value converted to in the first t year of purchase. β is the cost impact coefficient, which is negative.
The total cost
C(
T) includes the acquisition cost
Cbuy(
t) and maintenance cost
Copr(
t). The acquisition cost is the converted residual value of the vehicle plus the tax value, as shown below:
where
Cp(
t) is the selling price of the vehicle (tax included).
Cs(
t) is a tax on the purchase of a vehicle (electric vehicles are exempt).
rdep is the vehicle depreciation rate.
τ is the estimated service life of the vehicle.
Maintenance cost
Copr(
t) refers to the maintenance cost during the service period (three years free warranty for conventional fuel vehicles, increasing maintenance cost after three years, lifetime warranty for electric vehicles), which is expressed as follows:
where
Cm represents the increasing part of vehicle annual maintenance cost.
The prediction process of private electric vehicle ownership based on the improved Bass model is shown in
Figure 8. Considering the external and internal influencing factors of the electric vehicle as well as the price advantage of the electric vehicle, the ownership of the electric vehicle in this region each year is obtained through simulation.
3.3. Simulation Analysis of Electric Vehicle Ownership in Xinjiang
The method proposed in this paper is used to forecast the ownership of electric private vehicles in Xinjiang Province.
Figure 9 and
Table 4 show the forecast results of electric private vehicle ownership under different policy intensity and media publicity intensity. In the short term, there is little difference in the ownership of electric private vehicles. However, as time goes by, the promotion effect of policy support and media publicity on electric private vehicles gradually appears, and the effect of compulsory measures is the most obvious.
Figure 10 and
Table 5 show the forecast results of electric vehicle private vehicle ownership under different electric vehicle technology upgrading degrees, with the improvement of electric vehicle technology and infrastructure, electric vehicle customer satisfaction increases, which can promote electric vehicle sales.
Assuming that the initial value of the coefficient q0 = 0.5, initial value of innovation coefficient p0 = 0.001, technical maturity T0 = 0.01 of electric vehicles in 2019, technical update degree = 0.1.
The basic scene is set as that the fire ban policy has not been implemented in Xinjiang. The radical scene is that the Xinjiang Government will adopt the points reward policy in 2023, and the whole Xinjiang will begin to ban burning in 2028. At the same time, the key technologies and infrastructure construction of new energy vehicles will be accelerated from 2025. In addition, due to a large number of purchases of oil-powered vehicles around 2010, fuel-powered vehicles will begin to be scrapped in large quantities in 2030 based on the average service life of oil-powered vehicles of 20 years, and the number of replaced electric private vehicles will increase. Since 2015, the growth rate of fuel vehicles has declined, so the number of replacements of electric vehicles has decreased.
Figure 11 shows the forecast chart of electric vehicle ownership in Xinjiang by 2038, and
Table 6 shows the electric vehicle ownership in Xinjiang by 2038. In the basic scene, the total number of electric vehicles in Xinjiang will be 1,690,700 by 2038, accounting for 5.4% of the total number of private vehicles. Under the radical scene, the total number of electric vehicles in Xinjiang will be 6,437,900 by 2038, accounting for 86.7% of the total number of private vehicles. The model can accurately reflect the role of media publicity, policy subsidies and electric vehicle-related infrastructure in popularizing private electric vehicles.
In the early stage, the subsidy policy can play a significant role in increasing the market share of electric vehicles, so that electric vehicles have a certain internal growth capacity in the development process. Through policy support, electric vehicles development can be maintained at a high speed, but this development is not sustainable. With the intensification of market competition, the reduction of purchase costs brought by technological upgrading will become normal, and the preferential price will no longer arouse attention on the market. Therefore, the Government needs to seek new schemes to relay the subsidy policy.
The Government can appropriately increase the incentive mechanism to promote the vehicle enterprises to speed up technological upgrading and enhance the enthusiasm of technological innovation; reasonably increasing the “privilege” of electric vehicles in traffic and using public media to publicize the advantages of electric vehicles and the positive reputation provided by existing buyers can greatly influence the purchase decisions of imitators in the social system; enterprises and public institutions promote electric special vehicles, improve the market penetration in the special field, improve the visibility and user satisfaction of electric vehicles, implement a commercial application to drive the development of social electric vehicles to have a demonstration effect.
In the future, consumers will pay more attention to the cost performance of products, and new energy vehicles with high-cost performance will have an overwhelming advantage in the market. Only through technical guidance can electric vehicles have market competitiveness, can the sustained growth of electric vehicles be promoted. At present, there is still a need to solve the battery technology problems, and gradually improve the electric vehicle charging infrastructure construction.
The research and development in the field of the battery should be strengthened, and the standardization among various manufacturers in the industry should be unified, so as to improve the versatility of products, so as to realize scale economy and maximum resource sharing and utilization. The scale economy effect can better promote the production enterprises actively study and develop new technology, new equipment, and improve the competitiveness of enterprises. The improvement of battery equipment technology will increase the range of driving, shorten the charging time, extend the battery cycle life, improve the safety performance, improve the vehicle environment, enhance user satisfaction, greatly increase the public’s awareness of electric vehicles, and promote the production and marketing of electric vehicles in society.