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In this work, a dynamically loaded hydrodynamic journal bearing test rig is developed and introduced. The rig is a novel design, using a hydraulic actuator with fast acting spool valves to apply load to a connecting rod. This force is transmitted through the connecting rod to the large end bearing which is mounted on a spinning shaft. The hydraulic actuator allows for fully variable control and can be used to apply either static load in compression or tension, or dynamic loading to simulate engine operation. A variable speed electric motor controls shaft speed and is synchronized to the hydraulic actuator to accurately simulate loading to represent all four engine strokes. A high precision torque meter enables direct measurements of friction torque, while shaft position is measured via a high precision encoder.

Improving vehicle response through advanced knowledge of traffic behavior can lead to large improvements in energy consumption for the single isolated vehicle. This energy savings across multiple vehicles can even be larger if they travel together as a cohort in harmonization. Additionally, if the vehicles have enough information about their immediate path of travel, and other vehicles’ in that path (and their respective critical forward-looking information), they can safely drive close enough to each other to share aerodynamic load. These energy savings can be upwards of multiple percentage points, and are dependent on several criteria. This analysis looks at criteria that contributes to energy savings for a cohort of vehicles in synchronous motion, as well as describes a study that allows for better understanding of the potential benefits of different types of cohorted vehicles in different platoon arrangements.

The general benefits of automation are well documented. Order of magnitude improvements are achievable in processing speeds, production rates, and efficiency. Other benefits include improved process consistency (inversely, reduced process variation), reduced waste and energy consumption, and risk reduction to operators. These benefits are especially true for the automation of the aerospace paint removal (or "depaint") processes. Southwest Research Institute® (SwRI®) developed and implemented two systems in the early 1990s for depainting full-body fighter aircraft at Robins Air Force Base (AFB) at Warner Robins, Georgia, and Hill AFB at Ogden, Utah. These systems have been in production use, almost continuously for approximately 20 years, for the depainting of the F-15 Eagle and the F-16 Falcon fighter aircraft, respectively.

This paper presents an overview of the connected controls and optimization system for vehicle dynamics and powertrain operation on a light-duty plug-in multi-mode hybrid electric vehicle developed as part of the DOE ARPA-E NEXTCAR program by Michigan Technological University in partnership with General Motors Co. The objective is to enable a 20% reduction in overall energy consumption and a 6% increase in electric vehicle range of a plug-in hybrid electric vehicle through the utilization of connected and automated vehicle technologies. Technologies developed to achieve this goal were developed in two categories, the vehicle control level and the powertrain control level. Tools at the vehicle control level include Eco Routing, Speed Harmonization, Eco Approach and Departure and in-situ vehicle parameter characterization.

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.

Fuel is a significant portion of the operating cost for an on-highway diesel engine and fuel economy is important to the economics of shipping most goods in North America. Cat® ACERT™ engine technology is no exception. Ball bearings have been applied to the series turbochargers for the Caterpillar heavy-duty, on-highway diesel truck engines in order to reduce mechanical loss for improved efficiency and lower fuel consumption. Over many years of turbocharger development, much effort has been put into improving the aerodynamic efficiency of the compressor and turbine stages. Over the same span of time, the mechanical bearing losses of a turbocharger have not experienced a significant reduction in power consumption. Most turbochargers continue to use conventional hydrodynamic radial and thrust bearings to support the rotor. While these conventional bearings provide a low cost solution, they do create significant mechanical loss.

Horiba on-board diesel exhaust particulate sampler (OBS-PM) is a filter based partial flow particulate sampling system used for On-board diesel particulate matter (PM) measurement. It takes sample from either raw or diluted exhaust. It can run at constant dilution ratios or at variable dilution ratios with proportional control on the sample flow. The diluted exhaust moves through a pre-weighed 47 mm particulate filter and PM is collected on the filter. By weighing the loaded sample filter, PM emission from the engine or the vehicle can be determined. The performance of the OBS-PM meets most of requirements for a real-time partial flow sample system (PFSS) recommended by ISO 16183 [2]. The physical size and the power consumption of the instrument are minimized. It is powered with four 12 volts batteries, and can be installed on a vehicle for real-world PM emission evaluation.

Damping measurements on vehicle subsystems are rarely straightforward due to the complexity of the dynamic interaction of system joints, trim, and geometry. Various experimental techniques can be used for damping estimation, such as frequency domain modal analysis curve-fitting methods, time domain decay-rate methods, and other methods based on energy and wave propagation. Each method has its own set of advantages and drawbacks. This paper describes an analytical and an experimental comparison between two, widely used loss factor estimation techniques frequently used in Statistical Energy Analysis (SEA). The single subsystem Power Injection Method (PIM) and the Impulse Response Decay Method (IRDM) were compared using analytical models of a variety of simulated simple spring-mass-damper systems. Frequency averaged loss factor values were estimated from both methods for comparison.

Power split in Fuel Cell Hybrid Electric Vehicles (FCHEVs) has been controlled using different strategies ranging from rule-based to optimal control. Dynamic Programming (DP) and Model Predictive Control (MPC) are two common optimal control strategies used in optimization of the power split in FCHEVs with a trade-off between global optimality of the solution and online implementation of the controller. In this paper, both control strategies are developed and tested on a FC/battery vehicle model, and the results are compared in terms of total energy consumption. In addition, the effects of the MPC prediction horizon length on the controller performance are studied. Results show that by using the DP strategy, up to 12% less total energy consumption is achieved compared to MPC for a charge sustaining mode in the Urban Dynamometer Driving Schedule (UDDS) drive cycle.

SwRI has developed the DCO® ignition system, a unique continuous discharge system that allows for variable duration/energy events in SI engines. The system uses two coils connected by a diode and a multi-striking controller to generate a continuous current flow through the spark plug of variable duration. A previous publication demonstrated the ability of the DCO system to improve EGR tolerance using low energy coils. In this publication, the work is extended to high current (≻ 300 mA/high energy (≻ 200 mJ) coils and compared to several advanced ignition systems. The results from a 4-cylinder, MPI application demonstrate that the higher current/higher energy coils offer an improvement over the lower energy coils. The engine was tested at a variety of speed and load conditions operating at stoichiometric air-fuel ratios with gasoline and EGR dilution.

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.

Air conditioning and heating of heavy-duty truck cabs is an important contributor to engine efficiency, fuel economy and driver comfort. The air conditioner condenser coil and engine radiator typically share a common cooling fan, making it necessary to run the large engine cooling fan to provide condenser cooling. Engagement of the radiator cooling fan consumes a large amount of energy, further contributing to engine exhaust and noise emissions. Even under moderate temperature conditions, when the conventional engine-driven air conditioning compressor is not in use, the belt drive system adds a small speed-dependent parasitic load to the engine. Electrically driven air conditioning systems have the potential for lower energy consumption than their mechanical counterparts: Electrically driven air conditioning systems can reduce engine idle time by decoupling the air conditioner system from the engine cooling fan while offering near zero parasitic load when not in use.

Improved designs of extruded metal electrically heated catalysts (EHC) in combination with a traditional converter achieved the California ultra-low emission vehicle (ULEV) standard utilizing 50% less electrical energy than previous prototypes. This energy reduction is largely achieved by reducing the mass of the EHC. In addition to energy reduction, the battery voltage is reduced from 24 volts to 12 volts, and the power is reduced from 12 kilowatts to 3 kilowatts. Also discussed is the impact EHC mass, EHC catalytic activity, and no EHC preheating has on non-methane hydrocarbon emissions, energy requirements, and power requirements.

This paper describes installation and testing of electrified engine accessories and fuel cell auxiliary power units for a Class-8 tractor. A 2.4 kW fuel cell APU (Auxiliary Power Unit) has been added to supply a 42 V power supply for electrification of air conditioning and water pump systems. A 42/12 V dual alternator was used to replace the OEM alternator to provide safety back-up in case of fuel cell failure. A QNX Real Time Operating System-based (RTOS) Rapid Prototype Electronic Control System (RPECS™), developed by Southwest Research Institute (SwRI™), is used for supervisory control and coordination between accessories and engine. A Controller Area Network (CAN) interface, from the engine Electronic Control Unit (ECU), and the RS232 interface, from the fuel cell controllers, provide system data and control for RPECS. Custom wiring to the hydrogen, water pump, and air conditioning systems also provide data to RPECS. The water pump system controller is autonomous.

A series of road, engine, chassis dynamometer, and accessory power consumption tests was conducted in order to characterize the fuel economy of 1973 standard and intermediate size vehicles. Devices and systems which appeared to offer fuel economy benefits were evaluated by means of an analytical procedure. The study was limited to hardware which could be in production by the 1980 model year. The evaluation procedure was based on urban and steady speed operation, and the effects of compliance with future emission standards were included. Combinations of individual improvements were selected and applied to the same vehicle. The evaluation procedure was repeated, and fuel economy improvements of 30 to 70% were predicted by comparison with 1973 model year vehicles.

Numerous studies have demonstrated significant energy reduction for an ego vehicle by up to 20% leveraging Vehicle-to-Everything (V2X) technologies [1-4]. Some studies have also analyzed the impact of such vehicles on the energy consumption of other vehicles in a suburban or a highway corridor [5, 6], but the impact in an urban setting has not been studied yet. Southwest Research Institute (SwRI), in collaboration with Continental and Hyundai, is currently working on a Department of Energy funded project that is focused on quantifying the impact of multiple ego vehicles (smart vehicles) on the total energy consumption of the corridor under various traffic conditions, vehicle electrification level, vehicle-to-vehicle (V2V) technology penetration, and the number of smart (ego) vehicles in an urban setting. A six-kilometer-long urban corridor from Columbus, Ohio was modeled and calibrated with real-world data in PTV Vissim traffic microsimulation software.

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.

A detailed component performance, ratings, and cost study was conducted on series and parallel hybrid electric vehicle (HEV) configurations for several battery pack and main electric traction motor voltages while meeting stringent Partnership for a New Generation of Vehicles (PNGV) power delivery requirements. A computer simulation calculated maximum current and voltage for each component as well as power and fuel consumption. These values defined the peak power ratings for each HEV drive system's electric components: batteries, battery cables, boost converter, generator, rectifier, motor, and inverter. To identify a superior configuration or voltage level, life cycle costs were calculated based on the components required to execute simulated drive schedules. These life cycle costs include the initial manufacturing cost of components, fuel cost, and battery replacement cost over the vehicle life.

This paper presents real-world driving energy and fuel consumption results for the second-generation Chevrolet Volt plug-in hybrid electric vehicle (PHEV). A drive cycle, local to Michigan Technological University, was designed to mimic urban and highway driving test cycles in terms of distance, transients and average velocity, but with significant elevation changes to establish an energy intensive real-world driving cycle for assessing potential energy savings for connected and automated vehicle (CAV) control. The investigation began by establishing baseline and repeatability of energy consumption at various battery states of charge. It was determined that drive cycle energy consumption under a randomized set of boundary conditions varied within 3.6% of mean energy consumption regardless of initial battery state of charge.

This paper presents the development of a reduced-order powertrain model for energy and SOC estimation of a multi-mode plug-in hybrid electric vehicle using only vehicle speed profile and route elevation as inputs. Such a model is intended to overcome the computational inefficiencies of higher fidelity powertrain and vehicle models in short and long horizon energy optimization efforts such as Coordinated Adaptive Cruise Control (CACC), Eco Approach and Departure (EcoAND), Eco Routing, and PHEV mode blending. The reduced-order powertrain model enables Connected and Automated Vehicles (CAVs) to utilize the onboard sensor and connected data to quickly react and plan their maneuvers to highly dynamic road conditions with minimal computational resources.