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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.

Onboard sensing and external connectivity using Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) and Vehicle-to-Everything (V2X) technologies allows a vehicle to "know" its future operating environment with some degree of certainty, greatly narrowing prior information gaps. The increased development of such connected and automated vehicle systems, currently used mostly for safety and driver convenience, presents new opportunities to improve the energy efficiency of individual vehicles [1, 2, 3, 4, 5]. Southwest Research Institute (SwRI) in collaboration with Toyota Motor North America and University of Michigan is currently working on improving energy consumption of a Toyota Prius Prime 2017 by 20%. This paper will provide an overview of the various algorithms that are being developed to achieve the energy consumption target. Custom tools such as a traffic simulator was built to model traffic flow in Fort Worth, Texas with sufficient accuracy.

A new generation of vehicle dynamics and powertrain control technologies are being developed to leverage information streams enabled via vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) connectivity [1, 2, 3, 4, 5]. While algorithms that use these connected information streams to enable improvements in energy efficiency are being studied in detail, methodologies to quantify and analyze these improvements on a vehicle have not yet been explored fully. A procedure to test and accurately measure energy-consumption benefits of a connected and automated vehicle (CAV) is presented. The first part of the test methodology enables testing in a controlled environment. A traffic simulator is built to model traffic flow in Fort Worth, Texas with sufficient accuracy. The benefits of a traffic simulator are two-fold: (1) generation of repeatable traffic scenarios and (2) evaluation of the robustness of control algorithms by introducing disturbances.

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.