Next Article in Journal
Research on Braking Characteristics of Hybrid Excitation Rotary Eddy Current Retarder
Previous Article in Journal
Electric Vehicle Battery Remanufacturing: Circular Economy Leadership and Workforce Development
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
WEVJ
Volume 15
Issue 10
10.3390/wevj15100442
wevj-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Investigation and Analysis of the Contribution of Chinese Electric Vehicle Social Organizations’ Standardization Innovation to Intelligent Optimization Research and Development Investment

by
Linfeng Wu
1,*,
Chi Tian
2,
Yiming Liu
3,
Junhui Liu
4 and
Dan Cong
5
1
Institute of Standardization Theory and Strategy, China National Institute of Standardization, Beijing 100191, China
2
School of Electric Power, Shenyang Institute of Engineering, Shenyang 110136, China
3
School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China
4
Automobile Academy, Beijing Vocational College of Transportation, Beijing 102618, China
5
School of Law, North China Electric Power University, Beijing 102206, China
*
Author to whom correspondence should be addressed.
World Electr. Veh. J. 2024, 15(10), 442; https://doi.org/10.3390/wevj15100442
Submission received: 8 August 2024 / Revised: 18 September 2024 / Accepted: 24 September 2024 / Published: 28 September 2024
Browse Figures
Versions Notes

Abstract

:
Intelligent design has been the direction pursued by international electric vehicle (EV) research and development (R&D) teams in recent years. This paper analyzes the problems of unsustainable development in the current product design of EVs in China, such as high R&D investment, high innovation risks, and low R&D input–output ratios. It explores the issues related to intelligent design, R&D investment, car prices, and safety in the field of EVs in China, and it proposes the concept of optimizing intelligence to optimize the design investment of EVs in China. On the basis of the development situation and the existing problems of social organization standards that gather innovative technologies for EVs, this paper used data from the national social organization standard information platform as the research object and analyzed important data, such as the quantity of the information of relevant social organizations and professional fields of social organization standards, through mathematical methods. The article proposes an optimization design scheme for EV products in China, combining intelligence and practicality from the perspective of the optimizing intelligent design, and it models the construction of EV optimization design. The quantitative relationship between the two schemes before and after optimization design is compared in terms of cost savings in intelligent design, the improvement of social benefits, and the enhancement of EV cost performance. The comparative study found that intelligent optimization design reduced the R&D cost of EVs by 45.24%, and the social benefits of R&D investment increased by 29.51%.

1. Introduction

In recent years, with people paying attention to sustainable economic and social development, people’s concerns about environmental pollution have been increasing. Under the development requirements of “carbon peak, carbon neutrality”, the development of EVs has become a general trend both in China [1] and abroad [2]. Key features of EVs include environmental improvement, smooth driving, noiseless driving, a more enjoyable driving experience, and many more [3]. In addition, intelligent development has become obvious [4] in international EVs, as evidenced by the patterns seen in recent years in relevant government policies [5] and industrial policies [6] and the developmental trends in technologies such as autonomous driving [7], vehicle testing [8], and location recognition [9]. Similarly, with the rapid development of the Internet [10], big data [11], cloud computing [12], and artificial intelligence (AI) technologies [13], pure EVs in China are also following the development trend and gradually becoming intelligent [14], which is mainly reflected in the increasing application of human–vehicle interaction technology, intelligent networking technology, intelligent driving technology (including driving assistance technology and autonomous driving technology). There are 12 references to intelligentization in the “Development Plan for the New Energy Vehicle Industry (2021–2035)” [15], issued by the General Office of the State Council. With the extensive policy support from the Chinese government, many traditional car companies have transitioned into the EV field, while many non-traditional car companies (commonly known as new car-making forces, such as internet companies) have also joined the EV field of car manufacturing. Unlike traditional fuel-fired vehicles, EVs rely more on technological innovation, which has many uncertainties. The low input–output ratio is not conducive to the sustained and healthy development of the EV industry. According to data from Qcc.com, in the past two years, the number of closed enterprises related to EVs has risen annually, with approximately 52,500 businesses closing in 2023, marking an 88.2% year-on-year increase. Industry analysts primarily attribute this to two reasons: the lack of core technologies and the breaking of the capital chain. Therefore, resolving research and development funding are crucial for the survival of electric vehicle enterprises. How to improve the targeted investment of intelligent design(research) funds, how to better allocate limited funds to the most urgently needed areas, and how to quickly improve car performance without increasing prices are the issues that need to be studied. In addition, social organization standardization is a good approach for China and the EV technology market to demand technological innovation because China’s positioning of social organization standards is to meet market demand and carry out technological innovation. However, there are still some problems with the current social organization standards. This paper first statistically analyzes the factors affecting the competitiveness of the Chinese EV market and examines the input–output situation concerning its technological R&D and innovation. It then proceeds with a statistical analysis of the status of social organization standardization innovation in China’s EV industry. Subsequently, it delves into the issues surrounding investment in technological R&D and innovation and the process of social organization standardization innovation. Finally, on the basis of the theories of optimized design [16] and cost control [17] as theoretical foundations, the paper explores how to enhance the practical effectiveness of R&D and innovation investments and the efficiency of social organization standardization innovation under the trend of intelligence. The study also looks into ways to improve the cost–performance ratio of Chinese EVs so as to better benefit the international community. This research aims to change the current situation in which, under the trend of intelligence, there is an overemphasis on fancy yet impractical additional features, which impacts the realization of basic functions and the safety of EVs or results in overly high R&D and design costs, leading to higher car prices.

2. Literature Review

Firstly, we compiled studies on enhancing customer recognition of Chinese EVs. Rao Liang [18] believes that the promotion of new energy vehicles is constrained by problems such as high prices and inconvenient energy replenishment. Zhang Fang et al. [19], who studied the promotion model of Tesla EVs, believe that experience could be sought in the promotion of new energy vehicles in China. Tesla’s products pursue details and fashion. Its efficiency in supporting charging stations is much higher than that many of other brands. Moreover, the number of supercharging stations in China is rapidly increasing, which improves customer experience. Xia Yiming [20] proposed that EV companies should have an in-depth and comprehensive understanding of consumer demand, utilize the Internet of Vehicles system to achieve the intelligence and interconnectivity of internet-connected electric vehicles, position capital and production models, build complete charging facilities for consumers, and provide robust charging services. Additionally, they should adopt a dual-track marketing and communication strategy that combines online communication and dissemination with offline interactive experiences. Tang Baojun et al. [21] pointed out the existing problems in the construction of alternative power stations for EVs, such as inadequate infrastructure, low investment in R&D, and lack of unified government layout. They proposed suggestions to strengthen infrastructure development, increase R&D investment, and have the government provide an overall plan for the construction of battery swap stations. Fang Shan [22] summarized the problems of incomplete product layout, high prices, and single channels of NIO’s EVs and proposed marketing strategies to strengthen core technologies, accelerate product development and layout, improve user service levels, reduce product costs, consolidate the high-end EV segment market, and improve brand competitiveness. Ágota Bányai found that cross-docking the supply of electric vehicles can lead to energy-efficient solutions and emission reductions, and it is possible to achieve an improvement in energy efficiency of about 40% and a significant reduction in GHG(Greenhouse Gas) emissions of up to 30% [23].
Secondly, we compiled studies on the R&D investment [24], technological innovation [25], and intelligent design of EVs. For example, in terms of government funding to support enterprise R&D [26], the analyses of the relationship between input [27], output and efficiency [28]. Wang Hongqi et al. [29] believe that many EV companies in China attach importance to innovation, but technological uncertainty leads to risks. They suggested that BYD establish technical standards reduce technological dependence through cross-border alliance and collaboration and strive to meet consumers’ multifunctional needs according to market feedback. Yue Meiyi et al. [30] analyzed the current profit model of the BAIC EV Company and suggested collaborating with relevant parties in intelligent systems, autonomous driving, and power plant replacement. Wu Jianlong et al. [31] analyzed and studied the system construction process of NIO EVs and summarized NIO’s successful experience in R&D center construction, production chain division of labor, and application services.
Thirdly, we compiled studies on policy support for EVs in China, as well as the application of relevant methods or technologies in the field of EVs. Yu Jing [32] believes that in the future, EVs will achieve intelligentization, interconnectivity, and platformization. She proposed using financing leasing and time-sharing leasing to reduce the cost of car purchasing and provide convenience to consumers and, at the same time, to focus on consumer-centered communication and experiential marketing, establishing good communication with consumers. Jieyi Lu [33] compared different industrial policies and implementation effects of pure EVs between China and the United States through five aspects: economic incentives, charging station construction, R&D support, government vehicle procurement, and industry influence; they proposed suggestions for mutual learning and reference. Zhu Yanyang et al. [34] explored the appropriate period for subsidy recession, and the differences and boundaries of hedging effects between the two types of intelligence were explored by Zhu Yanyang et al., who provided an appropriate time for the subsidy recession of EVs. Wang Yanqing et al. [35] studied the application of blockchain technology in the field of EVs to promote the development of EVs in data sharing, optimized scheduling, and intelligent management. Xiong Yongqing et al. [36] used listed Chinese EV companies from 2010 to 2019 as their research sample and applied a panel vector autoregressive model to analyze the dynamic impact of two types of “non-subsidy” policies on enterprise R&D investment at different development stages from two dimensions: significance and agility.
At present, most of the research on China’s pure EVs focuses on technological development, business models, corporate strategies, and other aspects. Relatively little research has been conducted from the perspective of standardization theory and method technological innovation of pure EVs in China. This paper analyzes the intelligent design, practical design, safety, and innovation of pure EV products in China using the relevant theories and methods of standardization and social organization standard innovation. This study conducted targeted research and analysis on the issues affecting the sustainable development of the industry in the context of the new trend of intelligence in the development of pure EV products in China in recent years, which has important practical significance. In related research, the intelligence of EVs was studied from the perspective of data management by Wang Yanqing et al. [35] focusing on the intelligent networking, information storage, safe payment of electric energy, and charging pile management of EVs. This article explores improving the accuracy and practical benefits of R&D investment in EVs. The sustainable development of the EV industry can only be achieved if EV companies eliminate continuous losses and consumers can buy safe and reliable products that meet their basic needs.

3. Materials and Methods

3.1. Data Source

The data were sourced from the national social organization standard information platform (platform for short) [37], the official websites of relevant automotive brands, the official website of Autohome [38], and China National Knowledge Infrastructure (CNKI) [39]. Through the platform, social organizations and social organization standard information related to EV design, manufacturing, and intelligence can be searched and exported in the national economic industry classification C3650 (EV Manufacturing) by using “new energy vehicles”, “EVs”, “automotive intelligence”, and “automotive design”. The deadline for querying data was 31 March 2023. The relevant financial annual reports were searched through the official websites of relevant car brands, and the relevant data, such as R&D investment, marketing cost, EV sales, and sales revenue. The performance, price and other parameter data of EV related brands were searched through the official website of Autohome. Relevant literature was collected through CNKI, and the search keywords mainly included “new energy vehicle design”, “EV design”, “intelligent EV”, and “EV design”.

3.2. Data Processing

A MySQL database was established through mathematical data analysis software, eliminating irrelevant social organization standards on the basis of the names of the standards and descriptions of their main technical content, and information such as standard names, standard numbers, social organization names, certification authorities, activity regions, release dates, national economic classifications of social organization standards related to EV design, manufacturing, and intelligence was inputted. A mathematical analysis of the social organization level, certification province, social organization standard type, and professional fields involved was conducted. The financial data found on the official websites of relevant automotive brands was organized and analyzed, including their R&D investment, profits, and other data. The comprehensive statistical analysis software Stata was used to integrate and analyze existing data and statistical analysis was performed on issues related to social organization standardization innovation and R&D investment in Chinese EVs on the basis of the theories of optimized design and cost control. Mathematical and comparative analyses were conducted on the performance, price, and other parameter data of EV-related brands on the official website of Autohome. On the basis of relevant literature, the competitive factors of EVs compared to traditional fuel vehicles; the factors that affect consumer purchases; and the current investment situation, direction, and benefits of EV R&D in China were analyzed.

4. Analysis of EV Industry Development and Social Organization Standardization

According to research [40], statistics show that there are approximately 6 million highway traffic accidents on highways in the United States each year, resulting in approximately 35,000 deaths, and the direct economic losses caused by traffic accidents each year are as high as 230.6 billion USD. Intelligent design means the use of more auxiliary driving sensors. On the one hand, intelligence can improve security and reduce accidents caused by human error in operations. For example, intelligent connected vehicle security applications utilize dedicated short-range communication technology to achieve the safety pre-warnings of vehicle-to-vehicle and vehicle-to-road, achieving the goal of reducing or completely preventing traffic accidents [41]. However, too much intelligent design may also reduce security. An example is intelligent and electronic window glass control. When a vehicle falls into the water or becomes excessively damp, the electronic control of window opening fails, which poses a threat to life. In addition, in the context of high demand for sensors and the need to reduce costs, EV manufacturers have to adopt sensors with low quality and low reliability. In the event of sensor failure and excessive user dependence, it is extremely easy to cause traffic accidents.
Intelligence, an important direction in the R&D of EVs in China, makes cars intelligent and convenient, but it has also led to varying degrees of increase in the cost and price of EVs in China. However, practicality, which includes strong maneuverability, high safety, low price, and convenient use of EVs, should be considered. Blindly pursuing intelligence may lead to excessive R&D investment and unreasonable allocation. It is important to consider omitting and simplifying some aspects of intelligent R&D investment and functional design, appropriately improving the practicality and cost-effectiveness of EVs, and reducing costs of Chinese EVs. A balance between the intelligence and practicality of Chinese EVs is needed to optimize design, that is, to achieve moderate intelligence. Only by significantly increasing the input–output ratio of EV R&D can we reduce the R&D costs of EV enterprises, lower the prices of EVs, enhance customer recognition, and improve the economic benefits of enterprises. Only by promoting further precise investment in R&D and forming a virtuous cycle can we achieve the sustainable development of the EV industry in China and around the world. Of course, for different classes of vehicles, there will be varying requirements for the level of intelligence. For example, regular vehicles tend to focus more on meeting basic performance standards, whereas premium vehicles have higher expectations for intelligence levels. The weights assigned to different indicators in the process of optimizing design also differ accordingly. The general idea or schematic diagram of this study is shown in Figure 1. The following is a specific analysis of the relevant research content.

4.1. Analysis of Market Environment Issues

4.1.1. Analysis of Car Buyers

Currently, EVs are mainly used for traveling over a short distance. Among many reasons for purchasing cars, the main factors that consumers consider are shown in Table 1 [42]. It can be seen that usage cost and policy support are the key factors affecting consumer behavior. In addition, with the overall trend of intelligent development in the Chinese automotive industry, the intelligence of EVs is also an important aspect of consumer concern. At present, cars are not only a means of transportation, but they have gradually evolved from mechanical products to mechatronics, mechanical and electrical intelligence, intelligent networks, and other high-tech products, which become providers and recipients of data generation, reception, and intelligence services [43]. Automotive products are developing toward new technology carriers, new mobile intelligent terminals, digitalization, and storage space and toward cross-border integration [44]. According to a study [45], the main and pressing contradiction facing the Chinese automotive industry is the growing demand for automotive product quality, mobility services and mobility safety, and the homogenization and low end of automotive products, the limited carrying capacity of road transportation resources, inadequate EV infrastructure, and incomplete data safety standards. Currently, the main sales targets of EVs in China are urban users, users with limited license plate issuance in the first tier, multiple car users in other cities, and novice users who pursue automotive power performance. However, under the current situation, there is still a gap between the comprehensive situation of EVs in China and the actual user demand, especially in terms of cost-effectiveness, which needs to be greatly improved.
Therefore, it is necessary to improve the accuracy of investment in the intelligent design of EVs in response to declining subsidies for EVs, users’ emphasis on their cost-effectiveness, and limited R&D funds. Firstly, priority should be given to determining the research direction to reduce the cost and price of EVs and enhance the competitiveness of EVs on the premise of ensuring their reliability. Next, let us look at the R&D investments of leading enterprises in China’s EV sector, as well as the latest directions of research and innovation in EVs in China (relevant social organization standards).

4.1.2. Analysis of R&D Investment and Output of Popular EV Manufacturers

This study focuse on the input of R&D personnel among leading Chinese EV enterprises, with a specific examination of BYD’s allocation, as detailed in Table 2. This indicates that in recent years, the proportion of employees dedicated to R&D within BYD’s total workforce has demonstrated an ascending trajectory. This pattern signifies a heightened emphasis on R&D capabilities and underscores the company’s commitment to technological advancement and innovation. BYD’s R&D personnel are spread across multiple crucial domains, encompassing battery technology, electric motor and control systems, intelligent connectivity, autonomous driving, vehicle lightweighting, and the application of new materials. In-depth research in these areas constitutes the core driving force behind enhancements in EV performance, cost reduction, and the advancement of EV intelligence. Next, we conducted a specific statistical analysis on the R&D investment and revenue of China’s top EV brands, as shown in Figure 2, and compared and analyzed them with top American EV brands. By observing the data in recent years, it can be seen that the R&D expenditure, operating revenue, R&D investment as a percentage of operating revenue, number of R&D personnel, percentage of R&D personnel, net profit, gross profit margin, and return on net assets of BYD have been increasing year by year.
Comparative Analysis: Comparing the R&D investment and output between BYD and Tesla in Figure 3, it can be observed that BYD’s R&D investment as a percentage of operating income has remained relatively stable over the years with a rising trend. In recent years, BYD’s R&D investment has been higher than Tesla’s R&D investment. On the other hand, Tesla’s R&D investment started at a high level but experienced a sharp decline and eventually stabilized. In terms of return on equity (ROE), BYD initially decreased and then increased, while Tesla gradually improved from negative to positive. BYD’s R&D investment return rate is gradually surpassing Tesla’s. Overall, BYD shows more stability in terms of R&D investment, output, and profitability.

4.2. Analysis of Social Organization Standardization Issues in the Field of EVs

4.2.1. Social Organizations’ Issues in the Field of EVs

As of 31 March 2023, 209 relevant standards in the field of EVs were published by 72 social organizations. Among them, 49 social organizations had issued three or fewer items, accounting for 68.06% of the total. Twelve social organizations had issued four to seven standards, representing 16.67%, while two organizations had issued eight to ten items, accounting for 2.78%. Eleven to twenty items had been issued by two organizations, representing 2.78%, while twenty-one or more standards had been issued by a single organization, accounting for 1.39%. The social organization situation is shown in Table 3.

4.2.2. Social Organization Standard Issues in the Field of EVs

(1)
Innovative wisdom of social organization standards
The “Regulations on the Management of social organization standards” jointly issued by the National Standardization Administration Commission and the Ministry of Civil Affairs has a relatively clear positioning for social organization standards, namely responding to market demand and technological innovation. Therefore, social organization standards should usually be a concentrated manifestation of innovative wisdom. However, innovation has uncertainty and may develop freely in various directions. As for the new forces in car manufacturing, there is a significant gap between them and traditional car companies in terms of basic technology and scientific research, but they also have certain advantages in intelligence, technological sense, and fashionable appearance. For example, leading new power brands such as NIO, LEADING IDEAL, and Xiaopeng have significantly enhanced their competitiveness through continuous growth. In the new environment, various new car-making brands are constantly emerging [46]. However, these are just some of the innovative inspirations that traditional car companies need. The spread of innovative thinking through social organization standards is an effective method and has an important role to play in promoting the comprehensive competitiveness of pure EVs in China.
(2)
Analysis of social organization Standards in the Field of Intelligent Design of EVs
Currently, China’s EVs integrate universal, enabling, and fundamental technologies, such as AI, big data and computing power, and the Internet of Things, involving changes in the automotive industry sector, infrastructure, commercial formats, and value models [10]. The social organization standards related to the intelligent design of EVs also involve relevant factors. Using the keyword “intelligence” to search for existing social organization standards, there are five items related to intelligent charging. For example, T/GDC 49-2020 [47] (GDC, the abbreviated code for the Guangdong Product Certification and Service Association), “EV Intelligent Charging System Part 3: Operation and Maintenance Management Specification”, released by the Guangdong Product Certification Service Association, stipulates the general principles, operation and maintenance services, personnel management, safety management, and document management of the operation and maintenance management specifications for EV intelligent charging systems. It is applicable to the whole process operation and maintenance management of EV charging piles and similar passenger vehicle charging pile installation. Using the keyword “design” to search for existing social organization standards, there are five standards related to charging and swapping equipment and spare parts. For example, T/CAEE 026-2020 [48] (CAEE, the abbreviated code for the China Electronic Equipment Technology Development Association), “Design Specification for EV Charging Stations and Charging Piles”, issued by the China Electronic Equipment Technology Development Association, stipulates the basic principles and main technical requirements that should be followed in the design of EV charging stations and charging piles. It is applicable to the design and construction of new, expanded, and rebuilt EV charging stations and charging piles, but it is not applicable to the design and construction of EV battery replacement stations. In addition, there is little discussion of the security issues that AI systems may pose.

5. Discussion

In response to the current security issues arising from AI systems, in January 2023, the National Institute of Standards and Technology (NIST) released the AI Risk Management Framework (AI RMF 1.0) [49]. It suggested that R&D organizations can use the document to design trustworthy AI to guide R&D organizations in reducing security risks and avoiding bias and other negative consequences when developing and deploying AI systems. In Section 3.2, Safety, it states, “Safety risks that pose a potential risk of serious injury or death call for the most urgent prioritization and most thorough risk management process”. In addition, in March 2023, the Standards Council of Canada (SCC) released a White Paper on the Status of Global AI Standardization and Implications for Canada. After analyzing the policy background and key initiatives involving AI in standardization organizations, such as ISO/IEC and IEEE (Institute of Electrical and Electronics Engineers), as well as in countries such as Canada, the UK, the US, Singapore, and China, it concluded with the following recommendations for Canada. It is recommended that the participation of SMEs in international standard-setting should be strengthened by enhancing openness, transparency, and multi-participation in the process of standard-setting and by identifying applicable standards and supporting their application on a global scale [50]. It is obvious that some foreign countries have realized the security risks of AI design, which need to be paid attention to. Gathering the wisdom of public innovation in a standardized way is an effective way to solve AI security problems.

5.1. Analysis of the Problem of Social Organization Standards in the Field of EVs in China

By the end of March 2023, the platform had registered 7304 social organizations and issued 54,909 standards for social organizations. There are 72 representative social organizations registered related to the EV field, and only 209 standards in fields related to EV design, manufacturing, and intelligence have been issued, accounting for only 0.38%. By sorting out and analyzing these social organizations in the field of EVs and their standardization activities, there are three main problems in the following aspects.

5.1.1. Inaccurate Positioning of Social Organization Standards in the Field of EVs

The design of EVs may involve modeling design, structural design, material design, dynamic design, and electronic control design (including electrification, intelligence, etc.), covering a wide range of aspects. At present, a large number of social organizations in the field of EVs registered on the platform lack in-depth research on bottleneck technologies related to the EV industry for the standardization activities of the social organization, which is not conducive to solving current problems. There are too many social organization standards that specify the type of requirements, including the type of specifications and the type of testing methods, and few related technologies that can really reduce the cost are transformed into social organization standards. One of the major factors affecting the competitiveness of EVs in comparison to conventional fuel vehicles is the high price. For example, there are more mature automotive modular design tools, which can greatly enhance the versatility of components. The relevant social organization standards-setting should be strengthened in terms of modular design, integrated design, and simplified design, which can greatly reduce the cost.

5.1.2. Insufficient Attention to Relevant Issues Related to EV Safety

EV safety should be one of the most important issues for EV design, such as emergency braking, electric shock protection, electrolyte leakage, automatic high-voltage cut-off, collision safety of energy storage systems, etc. The existing mandatory national standard GB 38031-2020 (EVs traction battery safety requirements) [51] should be met first, and the use of control systems with particularly high reliability should be studied as much as possible in these fields. For example, in the design of these links, it is advisable to consider the intervention of mechanical systems with relatively high stability to achieve the replacement of the electronic intelligent systems currently used in large numbers of these links. Even if it looks clumsy, unattractive, or takes up more space, it is still important to focus on prioritization from the perspective of improving safety and reliability so as to prevent the recurrence of a large number of serious safety accidents caused by the brake failure of some EVs in recent years.

5.2. Suggestions for the Optimal Design of EVs in China

By sorting out and briefly analyzing the problems in the development process of intelligent design of EVs in China, as well as the standardized and innovative activities of representative social organizations in the field of EVs registered on the platform, some of its problems were identified. Next, we discuss suggestions for optimizing and improving the design of EVs in China and conduct a quantitative comparative analysis of the social benefits before and after the optimization design.

5.2.1. Consolidation of the Concept of Optimizing Intelligent Design of EVs

Intelligent design has been the direction pursued by EVs in recent years. Both Chinese national policy documents and Chinese EV enterprises are pursuing intelligent design, but the pursuit of intelligent design should be rationalized, meaning that intelligent design should be optimized. Because of the broad range of directions involved in intelligent design, Figure 4 presents a sampling of the directions for the intelligent design of EVs both currently and the future. Excessive intelligent design can easily lead to excessive R&D investment and redundant design. Some of the infrequent functions should be simplified as much as possible to reduce sensor settings. However, in some critical aspects, especially those related to driving, braking, and escaping, that may endanger life safety, intelligence should be moderately reduced. This means reducing the use of low-reliability sensors or adopting more reliable mechanical structures or traditional simple structures, rather than applying intelligent design to every detail. This can effectively reduce the cost of R&D, and a larger proportion of the R&D funds can be used to overcome pivotal technical problems. This concept can be solidified through social organization standards by gathering innovative technologies, and it can be applied on a small scale first. If good results are achieved, this design concept can be continuously expanded to a larger scale. That is, the process of developing social organization standards is the first step, and then it can be considered to gradually transform these standards into national standards. Therefore, in the early stage, the Ministry of Industry and Information Technology can organize relevant automotive enterprises, R&D institutions, universities, and colleges to hold policy documents in the form of conferences or seminars, release relevant policy documents, and strengthen the multi-channel publicity of the news.

5.2.2. Model Construction of EV Optimization Design

The overall goal of the optimal design of EVs is to focus on cost reduction while emphasizing the improvement of user experience. The EV as a whole is a complex product, and its total design involves overall vehicle control, power system control, transmission system control, sound system control, the design of measurement and control systems, lighting system control, and so on. The user experience involves safety, control convenience, energy supplement, purchase and daily use cost, driving experience, etc. When designers optimize the design of EVs, they first classify these relevant aspects and extract relevant indicators. From the perspective of basic function realization, driving safety, experience enhancement, and additional function design, the basic function realization should be satisfied first, the design related to driving safety should be strengthened, and the additional auxiliary functions should be simplified so as to achieve the optimized design, as shown in Figure 5. By establishing a design-function-cost-benefit analysis model and adopting quantitative analysis methods, the study references optimized design [16] and cost control [17] theoretical approaches from related research on automobile optimization design, including multiobjective optimization problems [52] and parameter optimization of the automotive steering system [53]. This involves constructing an analytical model of the relationship between different design parameters and product performance, price, and user experience, comparing the advantages and disadvantages of relevant design schemes, and deriving a more optimized design solution. In addition, for vehicle models with different market positions, the design of indicator weights also needs to vary. For instance, for regular vehicles, the weight given to meeting basic performance indicators should be higher. However, for premium vehicles, there is a need to increase the weights assigned to aspects such as reliability design related to safety and the enhancement of the driving experience.

5.2.3. Efficiency Comparison of R&D Investment before and after Intelligent Optimization Design of EVs

In the case of limited funding for the intelligent design of EVs, if the funds are applied evenly to basic function implementation, driving safety, experience improvement, and additional function design, it may lead to insufficient funding for bottleneck technologies and excessive investment in the design of some less important areas. Optimizing design is a solution to this problem. Assuming that the funding for intelligent design of EVs is 10 million CNY, we adjusted the traditional average allocation of intelligent design funding to ensure the design funding related to driving and passenger safety first. Moreover, the auxiliary functional design that is not closely related to driving safety was simplified. For example, the changes in the specific R&D funding allocation before and after an optimization design are shown in Figure 6. It is estimated that the amount of R&D investment required decreases by 45.24% (a decrease of 4.524 million CNY), but the proportion of social benefits from R&D investment increases from 35.71% to 65.22%, an increase of 29.51%, nearly 30%. The efficiency comparison with the previous R&D investment after intelligent optimization design is shown in Table 4. The R&D funds saved in this way will be more used to improve security and basic performance. In addition, by reducing expenses unrelated to driving safety, more funds can be used to improve the endurance of EVs and research and develop new materials and processes for EV batteries, thereby reducing the cost and price of EV R&D and enhancing the competitiveness of EVs compared with traditional fuel vehicles, which can facilitate the gain of more recognition from consumers.

6. Conclusions

According to the relevant research above, it can be seen that the price, performance, and convenience of the use of EVs are key factors that affect consumer purchasing (or the competitiveness of EVs compared to traditional fuel vehicles). At present, Chinese EV companies have a large amount of R&D investment from the government and enterprises themselves. Technological innovation is an important path to enhancing the cost performance of China’s EVs. Innovation is uncertain and requires guidance, particularly to ensure its success. In the current situation, in which China’s subsidy policies related to EVs are declining, it is necessary to study and consider more technologies and methods that can enhance the cost performance of EVs themselves. Intelligence is an important direction for the development of EVs in China and the world. The intelligent design of EVs plays an important role in simplifying driving operations, optimizing road selection, and improving electric control performance. However, practicality, safety, and low price should also be important directions to consider in the design of EVs in China. There is a great need for innovative technology development, application, and promotion in these areas. Long-term losses are not conducive to the sustainable and healthy development of EVs in China or internationally. The potential of social organization standards as a collection of innovative technologies should be better explored. Social organizations in related fields in China should shoulder the responsibility of joint research to better play the role of spreading the concept of optimizing intelligent design in the field of EVs. This can guide all sectors of society to improve the relevance of technology R&D and reduce R&D costs. The relevant departments of the Chinese government should also introduce relevant incentive and evaluation policies as soon as possible to improve the relevance of China’s EV R&D investment, stimulate the transformation of public innovation and wisdom, and improve the safety and practicality of China’s EVs. At the same time, this will lower the price of China’s EVs and better serve the international markets. There are certain limitations to this study, such as the need to optimize the design of R&D investment plans and conduct more in-depth research and analysis based on the most urgent needs and the research foundation of industrial development.

Author Contributions

Conceptualization, L.W. and Y.L.; methodology, L.W. and C.T.; investigation, L.W. and J.L.; writing—original draft preparation, L.W. and Y.L.; writing—review and editing, C.T. and D.C.; supervision, Y.L. and C.T.; project administration, L.W.; funding acquisition, L.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by China National Institute of Standardization under grant number 572024Y-11782.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Ouyang, M. Innovation and development of EVs for carbon neutrality. Sci. Chin. 2021, 467, 26–31. [Google Scholar]
  2. Diampovesa, S.; Hubert, A.; Yvars, P.A. Designing physical systems through a model-based synthesis approach. Example of a Li-ion battery for electrical vehicles. Comput. Ind. 2021, 129, 103440. [Google Scholar] [CrossRef]
  3. Patil, L.N.; Khairnar, H.P. Investigation of perceived risk encountered by electric vehicle drivers in distinct contexts. Appl. Eng. Lett. 2021, 6, 69–79. [Google Scholar] [CrossRef]
  4. Editorial Department of China Journal of Highway and Transport. Review on China’s Automotive Engineering Research Progress: 2023. China J. Highw. Transp. 2023, 36, 1–192. [Google Scholar]
  5. Srivastava, A.; Kumar, R.R.; Chakraborty, A.; Mateen, A.; Narayanamurthy, G. Design and Selection of Government Policies for Electric Vehicles Adoption: A Global Perspective. Transp. Res. Part E Logist. Transp. Rev. 2022, 161, 102726. [Google Scholar] [CrossRef]
  6. Wang, M. Research on China’s New Energy Vehicle Industry Policy. Doctoral Dissertation, Jilin University, Changchun, China, 2023. [Google Scholar]
  7. Munir, F.; Azam, S.; Rafique, M.A.; Sheri, A.M.; Jeon, M.; Pedrycz, W. Exploring ther malimages for objectd etection in underexposure regions for autonomous driving. Appl. Soft Comput. 2022, 121, 108793. [Google Scholar] [CrossRef]
  8. Danzer, A.; Griebel, T.; Bach, M.; Dietmayer, K. 2D car detection in radar data with PointNets. In Proceedings of the 2019 IEEE Intelligent Transportation Systems Conference (ITSC), Auckland, New Zealand, 27–30 October 2019; pp. 61–66. [Google Scholar]
  9. Hausler, S.; Garg, S.; Xu, M.; Milford, M.; Fischer, T. Patch-NetVLAD: Multi-scale fusion of locally-global descriptors for place recognition. In Proceedings of the 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, TN, USA, 20–25 June 2021; pp. 14136–14147. [Google Scholar]
  10. Li, P. Study on Mechanism of Disruptive Innovation; Economic Management Publishing House: Beijing, China, 2017. [Google Scholar]
  11. Jia, G. The Third Industrial Revolution and New Thinking of the New Path to Industrialization: Based on the Perspective of Evolutionary Economics and Economic History. J. Renmin Univ. China 2013, 27, 43–52. [Google Scholar]
  12. Li, P.; Deng, Z.; Zhang, Y. The Global Computing Power Competition Pattern under the New Sci-Tech Revolution and Industrial Transformation and China’s Countermeasures. Econ. Rev. J. 2021, 425, 33–42. [Google Scholar]
  13. Zhao, F.; Liu, Z.; Hao, H. Characteristics, trends and opportunities in changing automotive industry. J. Automot. Saf. Energy 2018, 9, 233–249. [Google Scholar]
  14. Zhao, F.; Liu, Z.; Li, Z. Development Mode and Implementation Strategy of Automotive Product Platform and Modularity. Automob. Technol. 2017, 501, 1–6. [Google Scholar]
  15. General Office of the State Council. The General Office of the State Council on the Issuance of the New Energy Vehicle Industry Development Plan (2021–2035). 2020. Available online: http://www.gov.cn/zhengce/content/2020-11/02/content_5556716.htm (accessed on 12 January 2022).
  16. Gongyang, P.; Gaogao, S. Theory and Practice of Vehicle Optimization Design; Peking University Press: Beijing, China, 2013. [Google Scholar]
  17. Hiroshi, O.; Eiyo, K.; Il, K.D.; Suya, W. Toyota Product Development and Cost Design; Shanghai Jiao Tong University Press: Shanghai, China, 2019. [Google Scholar]
  18. Rao, L. Exploring the marketing and promotion strategy of new energy vehicles. J. Commer. Econ. 2015, 15, 54–55. [Google Scholar]
  19. Zhang, F.; Wang, Z.; Zhou, J. Research on the promotion strategy of new energy vehicles in China based on the Tesla promotion model. Price Theory Pract. 2015, 375, 97–99. [Google Scholar]
  20. Xia, Y. Research on Communication Strategy of Internet Electric Vehicle Industry; Jilin University: Changchun, China, 2019. [Google Scholar]
  21. Tang, B.; Wang, X.; Wang, B.; Wu, Y.; Zou, Y.; Xu, H.; Ma, Y. Analysis and Prospect of China’s New Energy Vehicles Industry Development Level. J. Beijing Inst. Technol. 2019, 21, 6–11. [Google Scholar]
  22. Fang, S. Study on the Marketing Strategy of Azure New Energy Vehicle; South China University of Technology: Guangzhou, China, 2020. [Google Scholar]
  23. Bányai, Á. Energy-efficiency and sustainability in cross-docking supply using e-vehicles. Appl. Eng. Lett. 2023, 8, 139–147. [Google Scholar] [CrossRef]
  24. Lu, G.; Wang, Z.; Zhang, C. Research on performance of subsidizing innovation for Chinese strategic emerging industry. Econ. Res. J. 2014, 49, 44–55. [Google Scholar]
  25. Zheng, J.; Zhao, H.; Li, Z. A research on new energy vehicle industry R&D subsidy under the policy of a double credits. Sci. Res. Manag. 2019, 40, 126–133. [Google Scholar]
  26. Kleer, R. Government R&D subsidies as a signal for private investors. Res. Policy 2010, 39, 1361–1374. [Google Scholar]
  27. Howell, S. Financing innovation: Evidence from R&D grants. Am. Econ. Rev. 2017, 107, 1136–1164. [Google Scholar]
  28. Li, L.; Wang, D. The economic impact of government R&D investment: An empirical an analysis based on Sci Bud-CGE model. Sci. Sci. Manag. S&T 2009, 30, 30–34. [Google Scholar]
  29. Wang, H.; Wang, Y.; Wu, J.; Liu, J. Evolution Mechanism of Innovation Ecosystem for New Energy Vehicles: Case of BYD New Energy Vehicles. China Soft Sci. 2016, 304, 81–94. [Google Scholar]
  30. Yue, M.; Yin, Z. Analysis of the Profit Model of China’s New Energy Vehicles under the New Normal Economy—Take BAIC New Energy as an example. Auto Time 2021, 351, 102–103. [Google Scholar]
  31. Wu, J.; Hao, M.; Huang, J. The Construction of Enterprise Innovation Ecosystem in the “Internet +” Environment—The Case Study of NIO NEV. Soft Sci. 2021, 35, 70–77. [Google Scholar]
  32. Yu, J. Research on the Current Market Situation of New Energy Vehicles and Their Marketing Strategies; Jinan University: Changchun, China, 2016. [Google Scholar]
  33. Lu, J. Comparing U.S. and Chinese Electric Vehicle Policies. Environ. Energy Study Inst. 2018, 6, 1–9. [Google Scholar]
  34. Zhu, Y.; Lu, J.; Zhang, S. Can intelligentization hedge the effect of purchase subsidy decrease for new energy vehicle? Based on computable general equilibrium (CGE) approach. Syst. Eng. Theory Pract. 2022, 42, 2426–2446. [Google Scholar]
  35. Wang, Y.; Zhou, J.; Cong, R.; Wang, L.; Huang, Y.; Chen, D. Research Status and Development of Blockchain Technology in Intelligent Management of Electric Vehicles. South. Power Syst. Technol. 2022, 16, 55–67. [Google Scholar]
  36. Xiong, Y.; Zhang, Q. R&D Investment Incentives of New Energy Vehicles’ Non-Subsidized Policies in China-Difference Analysis Based on the Regional Innovation Atmosphere. R&D Manag. 2022, 34, 81–94. [Google Scholar] [CrossRef]
  37. China National Institute of Standardization. National Social Organization Standard Information Platform. 2023. Available online: https://www.ttbz.org.cn/ (accessed on 16 December 2023).
  38. Auto Home Network. 2023. Available online: https://www.autohome.com.cn/ (accessed on 15 August 2024).
  39. The CNKI Net. 2023. Available online: https://cnki.net/ (accessed on 12 December 2023).
  40. Singh, S. Critical Reasons for Crashes Investigated in the National Motor Vehicle Crash Causation Survey; Tech. Rep.; National Highway Traffic Safety Administration: Washington, DC, USA, 2015.
  41. Editorial Department of China Journal of Highway and Transport. Review on China’s Automotive Engineering Research Progress: 2017. China J. Highw. Transp. 2017, 30, 69–70. [Google Scholar]
  42. MOB Research Institute. China New Energy Vehicle Industry Insight 2021. 2021. Available online: https://www.mob.com/mobdata/report/138 (accessed on 10 October 2023).
  43. Zhang, J.; Li, K. Report on the Development of National Intelligent Networked Vehicle Industry (2018); Social Science Literature Press: Beijing, China, 2019. [Google Scholar]
  44. Mid- and Long-Term Development Plan for the Automotive Industry. 2017. Available online: https://www.iea.org/policies/7907-mid-to-long-term-development-plan-for-the-automotive-industry (accessed on 15 December 2023).
  45. Li, Y. An Economic Analysis of the Innovation-Driven, Upgrading of China’s Automobile Industry; Sichuan University: Chengdu, China, 2021. [Google Scholar]
  46. Zhao, Z. Research on Marketing Communication of New Energy Vehicles in China; Jilin University: Changchun, China, 2022. [Google Scholar]
  47. T/GDC 49-2020; EV Intelligent Charging System Part 3: Operation and Maintenance Management Specification. Guangdong Product Certification and Service Associatio: Guangzhou, China, 2020.
  48. T/CAEE 026-2020; Design Specification for EV Charging Stations and Charging Piles. China Electronic Equipment Technology Development Association: Beijing, China, 2020.
  49. National Institute of Standards and Technology U.S. Department of Commerce. Artificial Intelligence Risk Management Framework (AI RMF 1.0); National Institute of Standards and Technology U.S. Department of Commerce: Gaithersburg, MD, USA, 2023. [CrossRef]
  50. Standards Council of Canada. White Paper: The State of Global AI Standardization and What It Means for Canada. 2023. Available online: https://www.scc.ca/en/news-events/news/2023/white-paper-state-global-ai-standardization-and-what-it-means-for-canada (accessed on 1 December 2023).
  51. GB 38031-2020; Electric Vehicles Traction Battery Safety Requirements. State Administration for Market Regulation, Standardization Administration of China: Beijing, China, 2020.
  52. Li, H.; Zhang, Q. Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II. IEEE Trans. Evol. Comput. 2009, 13, 284–302. [Google Scholar] [CrossRef]
  53. Zhao, J.; Bei, S.; Zhang, L. On PSO-based Parameter Optimization of Automotive Electric Power Steering System. J. Syst. Simul. 2011, 23, 2788–2792. [Google Scholar]
Wevj 15 00442 g001
Figure 1. Schematic diagram of optimizing intelligent design concept.
Figure 1. Schematic diagram of optimizing intelligent design concept.
Wevj 15 00442 g001
Wevj 15 00442 g002
Figure 2. The R&D input–output situation of BYD in recent years.
Figure 2. The R&D input–output situation of BYD in recent years.
Wevj 15 00442 g002
Wevj 15 00442 g003
Figure 3. A comparison of R&D investment and output between BYD and Tesla in recent years.
Figure 3. A comparison of R&D investment and output between BYD and Tesla in recent years.
Wevj 15 00442 g003
Wevj 15 00442 g004
Figure 4. Some development directions involved in the intelligent design of EVs.
Figure 4. Some development directions involved in the intelligent design of EVs.
Wevj 15 00442 g004
Wevj 15 00442 g005
Figure 5. EV optimization design process diagram.
Figure 5. EV optimization design process diagram.
Wevj 15 00442 g005
Wevj 15 00442 g006
Figure 6. Changes in the proportion of investment in intelligent design and R&D of EVs.
Figure 6. Changes in the proportion of investment in intelligent design and R&D of EVs.
Wevj 15 00442 g006
Table 1. Main considerations for Chinese EV owners when purchasing vehicles.
Table 1. Main considerations for Chinese EV owners when purchasing vehicles.
RankingThe Main Factors to ConsiderProportion
1.Low energy costs of EVs55.8%
2.Obtaining a license plate48.0%
3.Unrestricted travel restrictions for EVs35.0%
4.EVs are environmentally friendly30.0%
5.Enjoying subsidies25.0%
6.EVs are relatively intelligent23.0%
7.Better experience when driving EVs20.0%
Table 2. The R&D personnel input–output situation of BYD’s R&D in recent years.
Table 2. The R&D personnel input–output situation of BYD’s R&D in recent years.
Year201520162017201820192020202120222023
Number of R&D Personnel (10,000)2.142.382.753.113.583.584.046.9710.28
Percentage of R&D Personnel (%)10.8912.2913.6814.1215.6215.9514.0112.2314.61
Table 3. The number of standards issued by representative social organizations in the field of EVs.
Table 3. The number of standards issued by representative social organizations in the field of EVs.
Number of Published StandardsNumber of Social OrganizationsThe ProportionName of Social Organization and Number of Published Standards
Name of Social OrganizationNumber of Published Standards
1~34968.06%Omit
Beijing Automotive Industry Association		49
4~71216.67%7
Zhejiang Automotive Industry Technology Innovation Association7
China Standardization Association6
China Electronic Equipment Technology Development Association5
China Power Supply Society5
Jilin Automotive Electronics Association5
China Electrical Industry Association4
China Electrical Engineering Society4
Zhejiang Energy Industry Federation4
Guangdong Product Certification Service Association4
8~1022.78%Guangdong Provincial Association for Promoting the Application of Measurement and Control Technology and Equipment2
Guangdong Provincial Energy Research Association2
11~2022.78%China Electric Power Enterprise Federation17
Zhejiang Provincial Brand Building Promotion Association13
21~5017.14%Chinese Society of Automotive Engineers32
Table 4. Comparison of the efficiency of investment before and after intelligent optimization design.
Table 4. Comparison of the efficiency of investment before and after intelligent optimization design.
Intelligent Design of EVsBasic Performance and Safety Changes of EVsFunding for Intelligent Design of EVs (1 Million CNY)Proportion of Social Benefits of R&D InvestmentChanges in R&D Costs for EVsChanges in EV PricesIncrease in the Proportion of Social Benefits of R&D Investment
Before optimizing the design100%1035.71%100%100%29.51%
After optimizing the design100%5.47665.22%54.76%54.76%
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Wu, L.; Tian, C.; Liu, Y.; Liu, J.; Cong, D. Investigation and Analysis of the Contribution of Chinese Electric Vehicle Social Organizations’ Standardization Innovation to Intelligent Optimization Research and Development Investment. World Electr. Veh. J. 2024, 15, 442. https://doi.org/10.3390/wevj15100442

AMA Style

Wu L, Tian C, Liu Y, Liu J, Cong D. Investigation and Analysis of the Contribution of Chinese Electric Vehicle Social Organizations’ Standardization Innovation to Intelligent Optimization Research and Development Investment. World Electric Vehicle Journal. 2024; 15(10):442. https://doi.org/10.3390/wevj15100442

Chicago/Turabian Style

Wu, Linfeng, Chi Tian, Yiming Liu, Junhui Liu, and Dan Cong. 2024. "Investigation and Analysis of the Contribution of Chinese Electric Vehicle Social Organizations’ Standardization Innovation to Intelligent Optimization Research and Development Investment" World Electric Vehicle Journal 15, no. 10: 442. https://doi.org/10.3390/wevj15100442

Article Metrics

Back to TopTop