Evolution of heavy-duty vehicle fuel efficiency policies in major markets

Abstract

Heavy-duty vehicles contribute a significant and increasing portion of global greenhouse gas emissions. The objective of this study is to provide an overview of heavy-duty vehicle efficiency policies in major markets to better inform the global evolution of climate mitigation measures. The paper compiles information from those four nations that have adopted some form of heavy-duty vehicle fuel economy standards-China Japan, United States of America (USA), and Canada-plus the European Union. Despite widespread differences, the study finds that each jurisdiction used simulation modeling to some extent to minimize the cost of chassis-based compliance testing. Further, the study identified several common elements under development for the next round of policies, including (1) how to incorporate trailer manufacturers into existing regulatory structures, (2) how to add new test procedures to fully account for potential benefits from hybrids and advanced transmissions, and (3) how to address the tension between separate test procedures for fuel economy and conventional pollutants. The paper concludes with a discussion of opportunities and challenges for aligning national policies in the future.

Impact of Heavy-Duty Diesel Truck Activity on Fuel Consumption and Its Implication for the Reduction of Greenhouse Gas Emissions

“…The California Tractor-Trailer GHG regulation, which came into operation in 2010, applies to all tractors pulling box-type trailers at least 53 feet in length, and requires that they be equipped with both aerodynamic devices and low rolling-resistance tires. The advantage of these measures is that they induce significant fuel savings and offer a benefit to fleet operators ( 3 , 5 , 6 ), which have already reported fuel savings ( 7 ).…”

Application and Efficiency of a Series-Hybrid Drive for Agricultural Use Based on a Modified Version of the World Harmonized Transient Cycle

“…Existing energy efficiency and emissions evaluation cycles (e.g., the WHTC and the Worldwide Transient Vehicle Cycle (WTVC)) are currently designed to evaluate the performance of road vehicles, such as trucks and buses. To evaluate the efficiency of agricultural machines such as tractors, each researcher currently uses his own non-standardized methodology [45,49]. Due to this fact, it is practically impossible to compare such machines with each other.…”

“…Additionally, by altering the transmission of an off-road heavy-duty vehicle, its efficiency can be increased. It is hypothesized that a CVT can be replaced by highly effective electric motors [17,[38][39][40][41][42][43][44][45][46][47], thus achieving similar transmission effectiveness while reducing the number of parts that cause mechanical losses. In this study, a power-splitting method for a series-hybrid system is investigated.…”

Clustering-Based Neural Network for Carbon Dioxide Estimation

“…Anthropogenic global warming has been caused by the increasing carbon dioxide emissions in recent decades, which has affected the sustainable development of human society in many ways. Therefore, China has made a solemn commitment to peak its carbon dioxide (CO 2 ) emissions before 2030 and reach carbon neutrality by 2060 leading to a number of carbon reduction initiatives across all sectors, especially the transport sector which consumes more than half of global fuel emissions and releases nearly a quarter of all anthropogenic CO 2 emissions [1]. The research on carbon reduction in the transport sector has very important ecological values.…”

“…For reducing carbon emissions and contributing to the achievement of the carbon peaking and carbon neutrality goals of energy saving and emission reduction, the study of the relationship between fuel consumption and CO 2 of heavy-duty vehicles can help guide the optimization of vehicle construction and traffic route selection because heavyduty vehicles have contributed to almost half of vehicle CO 2 emissions though representing just 11% of motor vehicles [1]. Some studies analysed relevant impact factors into account to reach the construction of the energy reduction models.…”