The large sales volume and a great number of passenger car ownership in China have brought a series of environmental and energy problems. In response to these problems, Corporate Average Fuel Consumption and New Energy Vehicle Dual-credit Regulation has been put forward in China. However, it is found that although the purpose of the Dual-credit Regulation is controlling the fuel consumption and promoting the development of the energy vehicle market, the fuel consumption restriction for fossil-fueled passenger cars is relaxed compared to CAFC (Corporate Average Fuel Consumption) regulation alone. Moreover, this effect of relaxation is more obvious when the market share of new energy vehicles increases. To quantitatively estimate the relaxation effect of the fuel consumption restriction, a method of quantifying the relaxation effect is designed, and three different scenarios of new energy vehicle market development have been presumed in this paper. It is found that there are three main factors related to new energy vehicles that cause the relaxation of fuel consumption restriction, and the effect might become obvious and severe after 2025 if the market share of new energy vehicles develops very rapidly. These results may affect the development of the automotive industry and needed to be concerned.

To reduce greenhouse gas emissions from passenger vehicles, new energy vehicles are actively promoted by China’s government. Various power system types are being developed and their sales keep increasing. However, there is uncertainty about the greenhouse gas emission of different vehicle types. This paper studies the life cycle carbon emissions of passenger vehicles in China. A calculation model is established with consideration of all types of power systems, model classes, and electric driving ranges. In order to calculate and compare the effect of carbon emission reduction on all types of vehicles, a sensitivity analysis is conducted in two ways to study three of the main influencing factors. The results show the carbon emission-reducing effect of different factors on different stages in the life cycle. It is known that different influencing factors have different effects on these stages. Since there is a variation in different vehicle types, the carbon reduction effect caused by these factors is different for these vehicle types. This paper describes a sensitivity analysis of three main influencing factors and puts forward relevant policy recommendations to reduce the carbon emissions of passenger cars during their life cycle based on these results. It is necessary to take the vehicle life cycle as a whole for carbon emission management. The conclusions of this paper can be used for vehicle manufacturers to decide the focus of technology research, and also have important reference significance for enterprises when making life cycle carbon reduction strategies for their products. It is also of certain value for China to formulate a medium- and long-term carbon emission reduction strategy for the passenger car industry.

An L3 smart vehicle (L3 SV) could behave differently from human-driven vehicles due to its intelligent configuration and decision-making logic, and may consequently exert influences on traffic flow. In order to clarify the L3 SV’s traffic impacts and accelerate L3 SV implementation, this paper conducted an evaluation on the traffic efficiency and energy consumption influences of L3 SVs based on a microscopic traffic simulation. Taking Beijing as a case, the relevant traffic economic benefits were calculated with the help of the previously proposed traffic economic benefits model. Before modeling L3 SVs, a two-dimensional general modeling architecture for SVs was proposed. According to the architecture, the driving behavior model, as well as behavior selection models of L3 SVs, was eventually determined, based on which the intelligent driving model of L3 SVs was established. Urban expressways were selected as the simulation road type, and scenario analysis was conducted on various proportions of L3 SVs and L3 connected and autonomous vehicles (L3 CAVs), as well as the input traffic flow rates. It was found that L3 SVs can significantly reduce the travel time and energy consumption and enlarge the actual road capacity. The improvement will become particularly prominent under saturated or supersaturated traffic flow and increasing the proportion of L3 SVs and L3 CAVs can also amplify the effect of traffic optimization. The related economic benefit is considerable, which is CNY 3.104 billion a year based on Beijing’s travel and traffic conditions.

Greenhouse gas emissions are a critical concern for China’s automotive industry, especially for passenger cars due to their high sales’ volume. Recently, the trend towards connected and autonomous driving vehicles has been significant in the passenger car market. However, the impact of these systems on the life cycle emissions of vehicles remains unclear. This paper focuses on system function levels from driver assistance to full driving automation and studies their life cycle greenhouse gas emissions. This research establishes a component list for the hardware system and a material inventory. Then, this paper reveals significant differences in total system emissions at these technology levels, 540.1 kg for primary, 1318.7 kg for medium, and 2279.2 kg for advanced systems. Despite this difference, the total is less than 7.23% of the total vehicle emissions. To further reduce this portion of GHG emissions, it is recommended that vehicles favor millimeter-wave radar over solid-state LiDAR in their sensing system hardware, coupled with cameras as the primary sensing element. In addition, Intelligent Hardware Systems are not recommended for internal combustion engine passenger cars for optimal balance between functionality and environmental impact.