Hubei Province is major automobile province that represents the prospects for the new energy vehicle industry in China. In order to enhance the competitiveness of the new energy vehicle industry in Hubei Province, This paper employs the “diamond model” to construct the evaluation index system of the competitiveness of the new energy automobile industry in Hubei Province. Determining the weight of each evaluation index by entropy method, and then calculates the scores of each evaluation index of Hubei Province and other benchmarking cities. A comparative analysis is conducted to examine the competitive advantages and shortcomings of Hubei’s new energy vehicle industry. The results show that the competitiveness of the new energy vehicle industry in Hubei Province is at the upper-middle level in the country, and the industrial development foundation has obvious advantages over other provinces and cities. However, there are still problems such as lagging supporting infrastructure, insufficient motivation for innovation and development, and low degree of regional openness and marketization. Therefore, the government should speed up the construction of industrial infrastructure facilities, vigorously cultivate and introduce professional talents, increase the research and development of core technologies and create a good consumption environment.

In view of in-vehicle system environment, users need a variety of multimedia audio sources coexist, which is necessary to provide users with a unified interactive experience of in-vehicle multimedia services, so as to reduce users’ learning costs, and provide the ultimate audio-visual services. This paper describes an application design method that fosters a unified interactive experience for in-vehicle multimedia services by utilizing techniques such as integrated architecture, systematic hierarchical structure, and modular extraction to achieve multi-source audio fusion. The proposed method effectively addresses challenges including inconsistencies in user interaction experiences, seamless transitioning across applications, and the repetition of development for universal content modules that arise from the independent design of various audio sources, and effectively improves in-vehicle interactive experience, system interaction consistency and development efficiency.

The current vehicle performance benchmarking system is inadequate for the development needs of new energy products.This study proposes a innovative method for vehicle performance benchmarking. This method optimizes the selection process of core competitors and obtains key performance parameters and control strategies through a combination of competitor bus signal analysis and experimental bus data. The results indicate that the vehicle performance benchmarking method proposed in this study enhances metrics and control strategies and significantly improves the depth and breadth of vehicle performance benchmarking. It effectively fills the gaps in the performance benchmarking of new energy competitors and offers comprehensive support for the development of vehicle product performance.

In order to build low-temperature driving range conditions for electric vehicles, this paper utilizes the T-BOX cloud based big data platform for electric vehicles in natural user scenarios, selects speed-related parameters by application principal component analysis, obtaining kinematic fragments of low-speed, medium-speed and high-speed through cluster analysis methods, compares the difference in travel speed of trams at normal temperature and low temperature, establishes a speed curve suitable for low temperature test according to the probability density calculation results, and simultaneously extracts the information of ambient temperature, air conditioning grade and air conditioning temperature. The relationship between ambient temperature and air conditioning setting is analyzed, the ambient temperature and air conditioning setting information suitable for low temperature test are obtained. The results show that compared with normal temperature, the low-speed driving time is extended by 3%, the medium-speed and high-speed driving time are reduced by 2% and 1% respectively, and the ambient temperature setting to -22 ℃, the air conditioning level setting to 3, and the air conditioning temperature setting to 26 ℃ can represent the using scenarios of most users, finally building a low temperature driving rangeworking condition of electric vehicles which is closer to the user’s actual situation.

In order to improve the endurance of the vehicle, with the goal of reducing the vehicle’s wind resistance and optimizing its aerodynamic performance, taking the vehicle’s aerodynamic development process as the starting point, the fluid analysis software STAR-CCM+ is used to simulate the aerodynamic performance of a certain pure electric SUV model. Taking into account the principles of overall aerodynamic design, the definition of styling style, and engineering feasibility, multiple drag reduction optimization schemes are proposed from the perspectives of exterior styling and bottom guard plate. (1) Based on the principle of “front circle”, the airflow in the front bumper area is separated and optimized into a more body fitting surface, reducing the positive pressure and energy dissipation at the front; (2) Based on the “behind rear” principle, effective improvement of the airflow state at the rear end is achieved through tail wing sealing, partial downward pressure on the roof, inward retraction of the side wings in Y direction, partial upward movement of the tail light area, and optimization of the bottom profile of the rear bumper, which increased the negative pressure at the rear and further reduced the overall wind resistance of the vehicle; (3) By optimizing the aerodynamic wheel rims, flattened full coverage bottom guard plates, and other local details, the vortex shape in the wheel cavity area and the flow of bottom airflow are effectively improved, ultimately resulting in a drag reduction rate of over 30% for the SUV. The drag coefficient is controlled within 0.28, effectively reducing the overall drag coefficient of the vehicle, meeting the development needs of vehicle performance, and improving the endurance of the SUV model.

To address the problem of jerking phenomenon experienced by dual-clutch transmission vehicles at low speeds and to enhance dynamic response capabilities and shift quality, this paper investigates a specific passenger car equipped with a dual-clutch transmission. Utilizing the AVL-DRIVE driving quality evaluation system, shift tests are conducted under various driving modes. The results indicate significant differences in shift quality across different driving modes. Analysis is performed on the items with lower ratings, and optimization strategies are proposed, providing a reliable basis for automobile manufacturers to improve the overall vehicle quality.

In order to comprehensively understand the construction standards for intelligent connected vehicle closed proving grounds, this paper provides an in-depth analysis of the “Specification for the Management of Road Testing of Intelligent Connected Vehicles (Trial)” and related standards and regulations. The specific requirements for 14 tests of intelligent connected vehicles in closed proving grounds are summarized. The main contents of constructing the closed test field for intelligent networked vehicles are organized. According to the relevant requirements, the intelligent networking transformation of the Hainan Proving Ground has been completed from 3 aspects: park renovation, hardware equipment facility construction, and software platform construction. This transformation aims to meet all closed test requirements for intelligent connected vehicles, serving as a reference for the construction of closed proving grounds or the upgrade of traditional proving grounds into intelligent connected proving grounds.

Using the patent analysis method, this paper constructs the technical decomposition system of high definition map and localization technology. On the basis of full patent data processing, this paper analyzes the patent technology development status and competition pattern of high definition map and localization technology from the aspects of patent application situation, patent applicant distribution, patent technology composition. It combs the development of key branches of high definition map and localization technologies, and finally puts forward some suggestions for the development of high definition map and localization technologies.

In order to reduce the influence of driving fatigue on drivers in man-machine co-driving environment, this paper elaborates the mechanism of driving fatigue in man-machine co-driving environment, then analyzes the detection methods of driving fatigue from subjective and objective aspects, and introduces the alleviation methods of driving fatigue from active fatigue and passive fatigue. Finally, the deficiency of current research on driving fatigue detection and alleviation in man-machine co-driving environment is pointed out, and the prospect of research on driving fatigue detection and alleviation in man-machine co-driving environment is presented from the perspective of multi-feature and multi-mode fusion.

In order to analyze the current development status and trends of intelligent manufacturing scenarios in automotive industry, a macro analysis of automotive intelligent manufacturing scenarios is conducted based on the selection of automotive companies in the list of “2023 Intelligent Manufacturing Demonstration Factories and Excellent Scenarios”. This study is carried out from 3 dimensions: regional distribution, excellent scenarios, and typical scenarios by analyzing the content of intelligent manufacturing scenarios from 3 aspects: product lifecycle, production process, and supply chain. The development of intelligent manufacturing scenarios in the automotive industry reveals the following trends: In the short term, the focus of intelligent manufacturing in the automotive industry remains on the “production process.” There is a growing demand to explore the implementation of intelligent manufacturing scenarios in the “product lifecycle” and “supply chain”.