Andrew Moskalik

Force-deflection behavior of piezoelectric C-block actuator arrays

C-blocks are unique piezoelectric building blocks which can be combined in series or parallel to generate tailorable performance and exploit the advantages of bender and stack architectures. This paper presents a complete theoretical model that predicts the force-deflection behavior for any generic C-block actuator array configuration. An experimental investigation with five case studies is described that validates the model over a broad range of actuator prototypes and performance. This study characterizes the sensitivity of this class of actuator array with respect to material, geometric, and configuration parameters. The paper concludes with a comparison of the generic C-block architecture to the current state of art on a basis of absolute measures such as maximum force, deflection, and work and normalized measures such as effective stress, strain, and work per actuator volume. From this, it is concluded that C-blocks are a highly efficient, mid-range actuation technology.

Vehicle Component Benchmarking Using a Chassis Dynamometer

The benchmarking study described in this paper uses data from chassis dynamometer testing to determine the efficiency and operation of vehicle driveline components. A robust test procedure was created that can be followed with no a priori knowledge of component performance, nor additional instrumentation installed in the vehicle. To develop the procedure, a 2013 Chevrolet Malibu was tested on a chassis dynamometer. Dynamometer data, emissions data, and data from the vehicle controller area network (CAN) bus were used to construct efficiency maps for the engine and transmission. These maps were compared to maps of the same components produced from standalone component benchmarking, resulting in a good match between results from in-vehicle and standalone testing. The benchmarking methodology was extended to a 2013 Mercedes E350 diesel vehicle. Dynamometer, emissions, and CAN data were used to construct efficiency maps and operation strategies for the engine and transmission. These maps were used in EP As Advanced Light-duty Powertrain and Hybrid Analysis Tool (ALPHA) vehicle model, which showed a good agreement between the modeled fuel economy and dynamometer test results.

Investigating the Effect of Advanced Automatic Transmissions on Fuel Consumption Using Vehicle Testing and Modeling

In preparation for the midterm evaluation (MTE) of the 2022-2025 Light-Duty Greenhouse Gas (LD GHG) emissions standards, the Environmental Protection Agency (EPA) is refining and revalidating their Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool using newly acquired data from model year 2013-2015 engines and vehicles. ALPHA is a physics-based, forwardlooking, full vehicle computer simulation capable of analyzing various vehicle types with different powertrain technologies, showing realistic vehicle behavior, and auditing of all internal ener gy flows in the model. As part of the validation of ALPHA, the EPA obtained model year 2014 Dodge Chargers equipped with 3.6 liter V6 engines and either a NAG1 five-speed automatic transmission or an 845RE eight-speed automatic transmission. Vehicles were tested on a chassis dynamometer; test results showed eight-speed vehicles averaging 6.5% reduction in unadjusted combined city-highway fuel consumption compared to five-speed vehicles. In addition, an 845RE eight-speed transmission was obtained and tested in a standalone transmission test rig. The measured transmission parameters were used in ALPHA to simulate the behavior and fuel consumption of the eight-speed Dodge Charger. A companion model for the five-speed Charger was also constructed; the resulting simulated fuel consumption for both vehicles closely matched the test results. This paper uses the validated ALPHA model to predict the effectiveness improvement of real-world transmissions over a baseline circa 2008 four-speed transmission, and to predict further improvements possible from future eight-speed transmissions. To that end, transmission models for a four-speed automatic transmission and future eight-speed automatic transmissions were constructed, and ALPHA was used to predict the fuel consumption differences of a Dodge Charger equipped with these transmissions. A fuel consumption reduction of over 12% was predicted when comparing a future eight-speed transmission to a baseline four-speed. Predicted fuel consumption reduction was over 16% when the engines were resized to maintain a constant acceleration performance.

Characterization of the Fluid Deaeration Device for a Hydraulic Hybrid Vehicle System

The attractiveness of the hydraulic hybrid concept stems from the high power density and efficiency of the pump/motors and the accumulator. This is particularly advantageous in applications to heavy vehicles, as high mass translates into high rates of energy flows through the system. Using dry case hydraulic pumps further improves the energy conversion in the system, as they have 1-4% better efficiency than traditional wet-case pumps. However, evacuation of fluid from the case introduces air bubbles and it becomes imperative to address the deaeration problems. This research develops a bubble elimination efficiency testing apparatus (BEETA) to establish quantitative results characterizing bubble removal from hydraulic fluid in a cyclone deaeration device. The BEETA system mixes the oil and air according to predetermined ratio, passes the mixture through a cyclone deaeration device, and then measures the concentration of air in the exiting fluid. Test results indicate the ability of the cyclone deaeration device to remove large bubbles with near 100% efficiency, while elimination of small (less than 1 mm diameter) bubbles proved to be a challenge. The explanation is provided through application of Stokes Law that shows a strong relationship between bubble size and bubble rise velocity. The theoretical analysis provides clear guidance regarding pathways towards improving the effectiveness of removing small bubbles.

Estimating GHG Reduction from Combinations of Current Best-Available and Future Powertrain and Vehicle Technologies for a Midsized Car Using EPA's ALPHA Model

The Environmental Protection Agency’s (EPA’s) Advanced LightDuty Powertrain and Hybrid Analysis (ALPHA) tool was created to estimate greenhouse gas (GHG) emissions from light-duty vehicles[1]. ALPHA is a physics-based, forward-looking, full vehicle computer simulation capable of analyzing various vehicle types with different powertrain technologies, showing realistic vehicle behavior, and auditing of all internal energy flows in the model. The software tool is a MATLAB/Simulink based desktop application. In preparation for the midterm evaluation of the light-duty GHG emission standards for model years 2022-2025, EPA is refining and revalidating ALPHA using newly acquired data from model year 2013-2015 engines and vehicles. From its database of engine and vehicle benchmarking data EPA identified the most efficient, engines, transmissions and vehicle technologies, and then used ALPHA to model a midsized car incorporating combinations of these existing technologies which minimize GHG emissions. In a similar analysis, ALPHA was used to estimate the GHG emissions from future low-GHG technology packages potentially available in model year 2025. This paper presents the ALPHA model inputs, results and the lessons learned during this modeling and assessment activity.

Constructing Engine Maps for Full Vehicle Simulation Modeling

The Environmental Protection Agency (EPA) has collected a variety of engine and vehicle test data to assess the efectiveness of new automotive technologies in meeting greenhouse gas (GHG) and criteria emission standards and to monitor their behavior in real world operation. EPA’s Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created to estimate GHG emissions from vehicles using various combinations of advanced technologies and has been refned using data from testing conducted at EPA’s National Vehicle and Fuel Emissions Laboratory.

Benchmarking a 2016 Honda Civic 1.5-liter L15B7 Turbocharged Engine and Evaluating the Future Efficiency Potential of Turbocharged Engines

As part of the U.S. Environmental Protection Agencys (EPAs) continuing assessment of advanced light-duty automotive technologies to support the setting of appropriate national greenhouse gas standards and to evaluate the impact of new technologies on in- use emissions, a 2016 Honda Civic with a 4-cylinder 1.5-liter L15B7 turbocharged engine and continuously variable transmission (CVT) was benchmarked. The test method involved installing the engine and its CVT in an engine dynamometer test cell with the engine wiring harness tethered to its vehicle parked outside the test cell. Engine and transmission torque, fuel flow, key engine temperatures and pressures, and onboard diagnostics (OBD)/CAN bus data were recorded. This paper documents the test results for idle, low, medium and high load engine operation, as well as motoring torque, wide-open throttle torque and fuel consumption during transient operation using both EPA Tier 2 and Tier 3 test fuels. Particular attention is given to characterizing enrichment control during high load engine operation. Results are used to create complete engine fuel consumption and efficiency maps and estimate CO2 emissions using EPAs ALPHA full vehicle simulation model, over regulatory drive cycles. The design and performance of the 1.5-liter Honda engine are compared to several other past, present, and future downsized-boosted engines and potential advancements are evaluated.

Representing GHG Reduction Technologies in the Future Fleet with Full Vehicle Simulation

As part of an ongoing assessment of the potential for reducing greenhouse gas emissions of light-duty vehicles, the U.S. Environmental Protection Agency (EPA) has implemented an updated methodology for applying the results of full vehicle simulations to the range of vehicles across the entire fleet. The key elements of the updated methodology explored for this paper, responsive to stakeholder input on the EPAs fleet compliance modeling, include 1) greater transparency in the process used to determine technology effectiveness, and 2) a more direct incorporation of full vehicle simulation results. This paper begins with a summary of the methodology for representing existing technology implementations in the baseline fleet using EPAs Advanced Light-duty Powertrain (ALPHA) full vehicle simulation. To characterize future technologies, a full factorial ALPHA simulation of every conventional technology combination to be considered was conducted. The vehicle simulation results were used to automatically generate response surface equations (RSEs), enabling the use of a quick and easily implemented set of specific equations to estimate fleet-wide emissions in place of running time consuming full vehicle simulations for each potential technology package applied to each model in the fleet. Since the regressions were not extended to represent technology combinations that were not actually simulated, the emissions estimates produced from the RSEs match the ALPHA simulation results with a high degree of conformity. For each vehicle in the fleet, the reduction in emissions for a future technology package can be estimated using RSEs associated with the initial and final technology packages, and considering the particular vehicles weight, road load, and power. As part of the effectiveness assessment based on weight, road load, and power, this paper will also examine the effect of performance changes in the vehicles.

Use of the hypothetical lead (HL) vehicle trace: A new method for evaluating fuel consumption in automated driving

The regulation of fuel consumption and emissions around the world is based on standard drive (SD) cycles. Several autonomous or simple eco-driving methods of smoother driving and smaller acceleration and braking can violate the ± 2 MPH speed deviation regulation from the SD and hence they are currently not counted towards the vehicle fuel economy, even though they are acceptable from a traffic pattern perspective, namely following a vehicle at a safe and reasonable gap. This paper develops and suggests a prototypical vehicle velocity versus time trajectory that supersedes each SD cycle since the SD cycle is the vehicle trace from following a vehicle with the prototypical velocity trace. The prototypical velocity trace is named from now on as the Hypothetical Lead (HL) vehicle cycle. In essence, the HL cycle recreates the traffic conditions followed by the drivers of the standard drive cycles. Finally, the paper concludes with a demonstration of using the HL cycle for assessing the fuel economy benefits of autonomous following in relation to standard test cycles and limits on the following distances to ensure that the different drive traces follow the same prototypical traffic conditions in a reasonable and safe way for real world applications.