Abstract

Vehicle speed limiters (VSLs) are one of the strategies for reducing greenhouse gas (GHG) emissions from heavy-duty vehicles; they work by limiting peak vehicle speed. In the Federal Phase 2 Rule—GHG Emissions and Fuel Efficiency Standards for Medium- and Heavy-duty Engines and Vehicles, the greenhouse gas emission model (GEM) includes emission reduction credits for vehicles equipped with tamper-proof VSLs set at 55 to 65 miles per hour (mph). In this study, on-road testing of three class 8 combination tractor-trailers was conducted at various cruising speeds between 45 and 78 mph under steady conditions to evaluate the emission impacts of VSLs on heavy-duty vehicles. The three tested trucks were equipped with model year (MY) 2007 and newer engines and low-rolling-resistance tires on both the tractors and trailers. One truck was tested with a combined test weight of 35,000 lb and each of the other two trucks was tested with a combined test weight of 76,000 lb. A portable emission measurement system (PEMS) was used to measure carbon dioxide (CO2) emissions, and results showed that distance-based CO2 emission rates were dependent on both vehicle speed and engine revolutions per minute (rpm). Compared to average CO2 emission rates of approximately 1524 grams per mile (g/mile) at 78 mph for these test trucks, average CO2 emission rates at 51 mph were ~ 36% lower (approximately 978 g/mile) and represented the minimum distance-based (i.e., in g/mile) CO2 emission rates within the speed range evaluated for the three test trucks. Specifically, when decreasing speeds from 78 to 55 mph, CO2 emissions were between 0.7 and 2.6% lower per mph reduced. The emission benefits of using VSLs estimated from data in this study agree with the emission credits in the federal GEM. In addition, the quadratic relationship between CO2 emissions and vehicle speed measured for the three test trucks was used to corroborate updates to CARB’s EMission FACtor (EMFAC) 2017 model that were based on dynamometer testing; the measured trends from this VSL study support the predictions in that model.

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