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Vehicle-to-everything (V2X) communication, primarily designed for communication between vehicles and other entities for safety applications, is now being studied for its potential to improve vehicle energy efficiency. In previous work, a 20% reduction in energy consumption was demonstrated on a 2017 Prius Prime using V2X-enabled algorithms. A subsequent phase of the work is targeting an ambitious 30% reduction in energy consumption compared to a baseline. In this paper, we present the Eco-routing algorithm, which is key to achieving these savings. The algorithm identifies the most energy-efficient route between an Origin-Destination (O-D) pair by leveraging information accessible through commercially available Application Programming Interfaces (APIs). This algorithm is evaluated both virtually and experimentally through simulations and dynamometer tests, respectively, and is shown to reduce vehicle energy consumption by 10-15% compared to the baseline over real-world routes.

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.

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.

The California Air Resources Board (CARB)-funded Stage 3 Heavy-Duty Low NOX program focusses on evaluating different engine and after-treatment technologies to achieve 0.02g/bhp-hr of NOX emission over certification cycles. This paper highlights the controls architecture of the engine and after-treatment systems and discusses the effects of various strategies implemented and tested in an engine test cell over various heavy-duty drive cycles. A Cylinder De-Activation (CDA) system enabled engine was integrated with an advanced after-treatment controller and system package. Southwest Research Institute (SwRI) had implemented a model-based controller for the Selective Catalytic Reduction (SCR) system in the CARB Stage 1 Low-NOX program. The chemical kinetics for the model-based controller were further tuned and implemented in order to accurately represent the reactions for the catalysts used in this program.

Connected and automated driving technology is known to improve real-world vehicle efficiency by considering information about the vehicle’s environment such as traffic conditions, traffic lights or road grade. This study shows how the powertrain of a hybrid-electric vehicle realizes those efficiency benefits by developing methods to directly measure real-time transient power losses of the vehicle’s powertrain components through chassis-dynamometer testing. This study is a follow-on to SAE Technical Paper 2019-01-0116, Test Methodology to Quantify and Analyze Energy Consumption of Connected and Automated Vehicles [1], to understand the sources of efficiency gains resulting from connected and automated vehicle driving. A 2017 Toyota Prius Prime was instrumented to collect power measurements throughout its powertrain and driven over a specific driving schedule on a chassis dynamometer.

Conventional methods for determining automotive powertrain efficiency include (1) component-level testing, such as engine dynamometer, transmission stand or axle stand testing, (2) simulations based on component level test data and (3) vehicle-level testing, such as chassis dynamometer or on-road testing. This paper focuses on vehicle-level testing to show where energy is lost throughout a complete vehicle powertrain. This approach captures all physical effects of a vehicle driving in real-world conditions, including torque converter lockup strategies, transmission shifting, engine control strategies and inherent mechanical efficiency of the components. A modern rear-wheel drive light duty pickup truck was instrumented and tested on a chassis dynamometer. Power was measured at the engine crankshaft output, the rear driveshaft and at the dynamometer.

SAE Recommended Practice J1540 [1] specifies test procedures to map transmission efficiency and parasitic losses in a manual transmission. The procedure comprises two parts. The first compares input and output torque over a range of speed to determine efficiency. The second measures parasitic losses at zero input torque over a range of speed. As specified in J1540, efficiency of transmissions is routinely measured on a test-stand under steady torque and speed [2] [3]. While such testing is useful to compare different transmissions, it is unclear whether the “in-use” efficiency of a given transmission is the same as that measured on the stand. A vehicular transmission is usually mated to a reciprocating combustion engine producing significant torque and speed fluctuations at the crankshaft. It is thus a valid question whether the efficiency under such pulsating conditions is the same as that under steady conditions.

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.

A new diesel engine system adopting alternative combustion with rich and near rich combustion, and an airflow-dominant control system for precise combustion control was used with a 4-way catalyst system with LNT (lean NOx trap) to achieve Tier II Bin 5 on a 2.2L TDI diesel engine. The study included catalyst temperature control, NOx regeneration, desulfation, and PM oxidation with and without post injection. Using a mass-produced lean burn gasoline LNT with 60,000 mile equivalent aging, compliance to Tier II Bin 5 emissions was confirmed for the US06 and FTP75 test cycles with low NVH, minor fuel penalty and smooth transient operation.

An airflow-dominant control system was developed to provide precise engine and exhaust treatment control with low air fuel ratio alternative combustion. The main elements of the control logic include a real-time state observer for in-cylinder oxygen mass estimation, a simplified packaging scheme for all air-handling and fueling parameters, a finite state machine for control mode switching, combustion control models to maintain robust alternative combustion during transients, and smooth rich/lean switching during lean NOx trap (LNT) regeneration without post injection. The control logic was evaluated on a passenger car equipped with a 4-way catalyst system with LNT and was instrumental in achieving US Tier II Bin 5 emission targets with good drivability and low NVH.