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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.

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.

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.

Typical two-site storage-based SCR plant models in literature consider NH3 stored in the first site to participate in NH3 storage, NOx conversion and second site to only participate in NH3 storage passively. This paper focuses on quantifying the impact of stored NH3 in the second site on the overall NOx conversion for an ultra-low NOx system due to intra site NH3 mass transfer. Accounting for this intra site mass transfer leads to better prediction of SCR out NH3 thus ensuring compliance with NH3 coverage targets and improved dosing characteristics of the controller that is critical to achieving ultra-low NOx standard. The stored NH3 in the second site undergoes mass transfer to the first site during temperature ramps encountered in a transient cycle that leads to increased NOx conversion in conditions where the dosing is switched off. The resultant NH3 coverage fraction prediction is critical in dosing control of SCR.

This work is a part of medium-duty Low NOx technology development project with a focus on evaluating a combination of engine and advanced aftertreatment for 0.02 g/bhp-hr NOx regulation proposed by CARB (California air resource board). In this project, a control oriented chemical kinetics model of SCR (Selective catalytic reduction) was used in the aftertreatment controller that is susceptible to performance degradation due to hydrothermal and chemical aging. This paper focuses on modeling the NOx conversion and NH3 storage characteristics using a controls oriented SCR plant model which is further used for a model-based urea dosing scheme. A set of steady state reactor tests were used to calibrate the SCR performance at degreened, hydrothermal only and hydrothermal + chemical aging conditions and also to determine inhibition factors related to aging. The resultant model is capable of simulating SCR performance deterioration such as a reduction in NOx conversion and NH3 storage.

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.

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.

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.