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Technical Paper

Evaluating the Impact of Connected Vehicle Technology on Heavy-Duty Vehicle Emissions

2023-04-11
2023-01-0716
Eco-driving algorithms enabled by Vehicle to Everything (V2X) communications in Connected and Automated Vehicles (CAVs) can improve fuel economy by generating an energy-efficient velocity trajectory for vehicles to follow in real time. Southwest Research Institute (SwRI) demonstrated a 7% reduction in energy consumption for fully loaded class 8 trucks using SwRI’s eco-driving algorithms. However, the impact of these schemes on vehicle emissions is not well understood. This paper details the effort of using data from SwRI’s on-road vehicle tests to measure and evaluate how eco-driving could impact emissions. Two engine and aftertreatment configurations were evaluated: a production system that meets current NOX standards and a system with advanced aftertreatment and engine technologies designed to meet low NOX 2031+ emissions standards.
Technical Paper

Demonstration of Energy Consumption Reduction in Class 8 Trucks Using Eco-Driving Algorithm Based on On-Road Testing

2022-03-29
2022-01-0139
Vehicle to Everything (V2X) communication has enabled on-board access to information from other vehicles and infrastructure. This information, traditionally used for safety applications, is increasingly being used for improving vehicle fuel economy [1-5]. This work aims to demonstrate energy consumption reductions in heavy/medium duty vehicles using an eco-driving algorithm. The algorithm is enabled by V2X communication and uses data contained in Basic Safety Messages (BSMs) and Signal Phase and Timing (SPaT) to generate an energy-efficient velocity trajectory for the vehicle to follow. An urban corridor was modeled in a microscopic traffic simulation package and was calibrated to match real-world traffic conditions. A nominal reduction of 7% in energy consumption and 6% in trip time was observed in simulations of eco-driving trucks.
Journal Article

Cycle-Average Heavy-Duty Engine Test Procedure for Full Vehicle Certification - Numerical Algorithms for Interpreting Cycle-Average Fuel Maps

2016-09-27
2016-01-8018
In June of 2015, the Environmental Protection Agency and the National Highway Traffic Safety Administration issued a Notice of Proposed Rulemaking to further reduce greenhouse gas emissions and improve the fuel efficiency of medium- and heavy-duty vehicles. The agencies proposed that vehicle manufacturers would certify vehicles to the standards by using the agencies’ Greenhouse Gas Emission Model (GEM). The agencies also proposed a steady-state engine test procedure for generating GEM inputs to represent the vehicle’s engine performance. In the proposal the agencies also requested comment on an alternative engine test procedure, the details of which were published in two separate 2015 SAE Technical Papers [1, 2]. As an alternative to the proposed steady-state engine test procedure, these papers presented a cycle-average test procedure.
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