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Wind tunnel testing of reduced-scale models is a valuable tool for aerodynamic development during the early stages of a new vehicle program, when basic design themes are being evaluated. Both full-and reduced-scale testing have been conducted for many years at the General Motors Aerodynamics Laboratory (GMAL), but with increased emphasis on aerodynamic drag reduction, it was necessary to identify additional facilities to provide increased test capacity. With vehicle development distributed among engineering teams around the world, it was also necessary to identify facilities local to those teams, to support their work. This paper describes a cooperative effort to determine the correlation among five wind tunnels: GMAL, the Glenn L.

This investigation utilizes a DFSS analysis approach to determine automatic transmission gear content required to minimize fuel consumption for various powertrain - vehicle systems. L18 and L27 inner arrays with automatic transmission design and shift pattern constraint parameters were varied to determine their relative influence on fuel consumption. An outer noise array consisting of two vehicles with various engines, final drive ratios and legislated emissions test cycles was used to make a robust transmission selection based on minimizing fuel consumption. The full details of the DFSS analysis method and assumptions are presented along with a detailed examination of the results. With respect to transmission design parameters, parasitic spinloss and gear mesh efficiency were found to be most important followed by the number of gears. The DFSS analysis further revealed that unique transmission design formulations are potentially required for widely varying engines.

Accurately characterizing vehicle drive cycles plays a fundamental role in assessing the performance of new vehicle technologies. Repeatable, short duration representative drive cycles facilitate more informed decision making, resulting in improved test procedures and more successful vehicle designs. With continued growth in the deployment of onboard telematics systems employing global positioning systems (GPS), large scale, low cost collection of real-world vehicle drive cycle data has become a reality. As a result of these technological advances, researchers, designers, and engineers are no longer constrained by lack of operating data when developing and optimizing technology, but rather by resources available for testing and simulation. Experimental testing is expensive and time consuming, therefore the need exists for a fast and accurate means of generating representative cycles from large volumes of real-world driving data.

A rough road ride assessment provides an insightful evaluation of vehicle responses beyond the frequency range of suspension or steering modes. This is when body structure influence on the vehicle performance can be detected by vehicle occupants. In this paper, a rough road is used to evaluate vehicle ride performance and multi-body simulation (MBS) models are developed along with finite-element (FE) representations of the vehicle body and structure. To produce high fidelity simulation results in the frequency range of interest, various vehicle subsystem modeling contents are examined. A case study of a vehicle model with two different structures is provided. Time histories and frequency based analyses are used to obtain insights into the effects of body structure on vehicle responses. Finally, two metrics (‘Isolation’ and ‘Shake’) are used to distinguish the vehicle ride performance.

Turbulence is known to influence the aerodynamic and aeroacoustic performance of ground vehicles. What is not thoroughly understood are the characteristics of turbulence that influence this performance and how they can be applied in a consistent manner for aerodynamic design and evaluation purposes. Through collaboration between Transport Canada and the National Research Council Canada (NRC), a project was undertaken to develop a system for generating road-representative turbulence in the NRC 9 m Wind Tunnel, named the Road Turbulence System (RTS). This endeavour was undertaken in support of a larger project to evaluate new and emerging drag reduction technologies for heavy-duty vehicles. A multi-stage design process was used to develop the RTS for use with a 30% scale model of a heavy-duty vehicle in the NRC 9m Wind Tunnel.

AUTOSAR(AUTomotive Open System ARchitecture) establishes an industry standard for OEMs and the supply chain to manage growing complexity to the automotive electronics domain. Increased focus on software based features will prove to be a key differentiator between vehicle platforms. AUTOSAR serves to standardize automotive serial data communication protocols, interaction with respect to hardware peripherals within an ECU and allow ECU implementer to focus on development of unique customer focused features that distinguish product offerings. Adoption strategy and impact assessment associated with leveraging AUTOSAR for an E/E Architecture and the potential challenges that need to be considered will be described in this publication. This publication will also illustrate development strategies that need to be considered w.r.t deploying AUTOSAR like data exchange, consistency to BSW software implementation, MCAL drivers etc.

Hybrid electric vehicles, plug-in hybrid electric vehicles, and battery electric vehicles offer the potential to reduce both oil imports and greenhouse gases, as well as to offer a financial benefit to the driver. However, assessing these potential benefits is complicated by several factors, including the driving habits of the operator. We focus on driver aggression, i.e., the level of acceleration and velocity characteristic of travel, to (1) assess its variation within large, real-world drive datasets, (2) quantify its effect on both vehicle efficiency and economics for multiple vehicle types, (3) compare these results to those of standard drive cycles commonly used in the industry, and (4) create a representative drive cycle for future analyses where standard drive cycles are lacking.

A 2002 Cummins ISM engine was modified to be optimized for operation on gas-to-liquid (GTL) fuel and advanced emission control devices. The engine modifications included increased exhaust gas recirculation (EGR), decreased compression ratio, and reshaped piston and bowl configuration. The emission control devices included a deNOx filter and a diesel particle filter. Over the transient test, the emissions met the 2007 standards. In July 2004, the modified engine was installed into a Class 8 tractor for use by a grocery fleet. Chassis emission testing of the modified vehicle was conducted at the National Renewable Energy Laboratory's (NREL) Renewable Fuels and Lubricants (ReFUEL) facility. Testing included hot and cold replicate Urban Dynamometer Driving Schedule (UDDS) and New York Composite (NYComp) cycles and several steady-state points. The objective of the testing was to demonstrate the vehicle's with the modified engine.

Aerodynamic vehicle design improvements require flow simulation driven iterative shape changes. The 3-D flow field simulations (CFD analysis) are not explicitly descriptive in providing the direction for aerodynamic shape changes (reducing drag force or increasing the down-force). In recent times, aerodynamic shape optimization using the adjoint method has been gaining more attention in the automotive industry. The traditional DOE (Design of Experiment) optimization method based on the shape parameters requires a large number of CFD flow simulations for obtaining design sensitivities of these shape parameters. The large number of CFD flow simulations can be significantly reduced if the adjoint method is applied. The main purpose of the present study is to demonstrate and validate the adjoint method for vehicle aerodynamic shape improvements.

The Flight Research Laboratory (FRL), National Research Council (NRC) of Canada is currently developing an in-flight aircraft aerodynamic model identification technique that determines the small perturbation model at a given test condition. Initial demonstrations have been carried out using the NRC Falcon 20 research aircraft. An efficient system architecture, in terms of both software algorithms and hardware processing, has been designed to meet the stringent near real-time requirements of an in-flight system. As well, novel hardware and software techniques are being applied to the calibration and measurement of the fundamental in-flight parameters, such as air data. The small perturbation models are then combined to develop a global model of the aircraft that is validated by comparing the model response to flight data. The maneuvers were performed according to the FAA Acceptance Test Guide (ATG).

This paper presents the most recent advancement in the vehicle development process using the one-step or auto Transfer Path Analysis (TPA) in conjunction with the superelement, component mode synthesis, and automated multi-level substructuring techniques. The goal is to identify the possible ways of energy transfer from the various sources of excitation through numerous interfaces to given target locations. The full vehicle model, consists of superelements, has been validated with the detailed system model for all loadcases. The forces/loads can be from rotating components, powertrain, transfer case, chain drives, pumps, prop-shaft, differential, tire-wheel unbalance, road input, etc., and the receiver can be at driver/passenger ears, steering column/wheel, seats, etc. The traditional TPA involves two solver runs, and can be fairly complex to setup in order to ensure that the results from the two runs are consistent with subcases properly labeled as input to the TPA utility.

The application of cooperative adaptive cruise control (CACC) to heavy-duty trucks known as truck platooning has shown fuel economy improvements over test track ideal driving conditions. However, there are limited test data available to assess the performance of CACC under real-world driving conditions. As part of the Cummins-led U.S. Department of Energy Funding Opportunity Announcement award project, truck platooning with CACC has been tested under real-world driving conditions and the results are presented in this paper. First, real-world driving conditions are characterized with the National Renewable Energy Laboratory’s Fleet DNA database to define the test factors. The key test factors impacting long-haul truck fuel economy were identified as terrain and highway traffic with and without advanced driver-assistance systems (ADAS).

Aerodynamic interaction between vehicles on a roadway can modify the fuel use and greenhouse gas emissions of the vehicle relative to their performance under isolated, uniform-wind conditions. A comprehensive wind-tunnel study was undertaken to examine changes to the aerodynamic drag experienced by vehicles in close proximity, in adjacent lanes. Wind-load measurements were conducted for two general configurations: 15%-scale testing with light-duty-vehicle (LDV) models, and 6.7%-scale testing with a heavy-duty vehicle (HDV) model. For the LDV study, a DrivAer model was tested with a proximate AeroSUV model or an Ahmed model at lateral distances representing 75%, 100%, and 125% of a typical highway lane spacing, and for longitudinal distances up to 2 vehicle lengths forward and back. Commensurate measurements were conducted for the AeroSUV model with the proximate DrivAer or Ahmed model.

This paper describes an investigation of the performance potential of conventional flat-panel boat-tail concepts applied to tractor-trailer combinations. The study makes use of data from two wind-tunnel investigations, using model scales of 10% and 30%. Variations in boat-tail geometry were evaluated including the influence of length, side-panel angle and shape, top-panel angle and vertical position, and the presence of a lower panel. In addition, the beneficial interaction of the aerodynamic influence of boat-tails and side-skirts that provides a larger drag reduction than the sum of the individual-component drag reductions, identified in recent years through wind-tunnel tests in different facilities, has been further confirmed. This confirmation was accomplished using combinations of various boat-tails and side-skirts, with additional variations in the configuration of the tractor-trailer configuration.

Hazardous atmospheric icing conditions occur at sub-zero temperatures when droplets come into contact with aircraft and freeze, degrading aircraft performance and handling, introducing bias into some of the vital measurements needed for aircraft operation (e.g., air speed). Nonetheless, government regulations allow certified aircraft to fly in limited icing environments. The capability of aircraft sensors to identify all hazardous icing environments is limited. To address the current challenges in aircraft icing detection and protection, we present herein a platform designed for in-flight testing of ice protection solutions and icing detection technologies. The recently developed Platform for Ice-accretion and Coatings Tests with Ultrasonic Readings (PICTUR) was evaluated using CFD simulations and installed on the National Research Council Canada (NRC) Convair-580 aircraft that has flown in icing conditions over North East USA, during February 2022.

This paper presents the adhesion strength of ice on sanded and machine-finished aluminum test coupons as measured using the National Research Council of Canada (NRC) Altitude Icing Wind Tunnel (AIWT) spin rig. This rig is used to evaluate commercial and internally-developed coatings for low-adhesion properties, and the performance of ice on aluminum is required as a baseline to compare the coatings against. The tests are performed over a range of aerodynamic and icing cloud conditions, including variations in static air temperature and exposure time (and therefore accumulated ice mass). The data analysis includes an evaluation of the uncertainty in the results based on the measured ice mass repeatability and the measured shear stress repeatability.

This article presents an autonomous steering control scheme for articulated heavy vehicles (AHVs). Despite economic and environmental benefits in freight transportation, lateral stability is always a concern for AHVs in high-speed highway operations due to their multi-unit vehicle structures, and high centers of gravity (CGs). In addition, North American harsh winter weather makes the lateral stability even more challenging. AHVs often experience amplified lateral motions of trailing vehicle units in high-speed evasive maneuvers. AHVs represent a 7.5 times higher risk than passenger cars in highway operation. Human driver errors cause about 94% of traffic collisions. However, little attention has been paid to autonomous steering control of AHVs.

While it is well known that “MPG will vary” based on how one drives, little independent research exists on the aggregate fuel savings potential of improving driver efficiency and on the best ways to motivate driver behavior changes. This paper finds that reasonable driving style changes could deliver significant national petroleum savings, but that current feedback approaches may be insufficient to convince many people to adopt efficient driving habits. To quantify the outer bound fuel savings for drive cycle modification, the project examines completely eliminating stop-and-go driving plus unnecessary idling, and adjusting acceleration rates and cruising speeds to ideal levels. Even without changing the vehicle powertrain, such extreme adjustments result in dramatic fuel savings of over 30%, but would in reality only be achievable through automated control of vehicles and traffic flow.

Some CO2-reducing technologies have real-world benefits not captured by regulatory testing methods. This paper documents a two-layer heating, ventilation, and air-conditioning (HVAC) system that facilitates faster engine warmup through strategic increased air recirculation. The performance of this technology was assessed on a 2020 Hyundai Sonata. Empirical performance of the technology was obtained through dynamometer tests at Argonne National Laboratory. Performance of the vehicle across multiple cycles and cell ambient temperatures with the two-layer technology active and inactive indicated fuel consumption reduction in nearly all cases. A thermally sensitive powertrain model, the National Renewable Energy Laboratory’s FASTSim Hot, was calibrated and validated against vehicle testing data. The developed model included the engine, cabin, and HVAC system controls.

A joint program between Bell Helicopter Textron Canada and the Flight Research Laboratory of Canada's National Research Council was initiated to address the aerodynamic modelling challenges of the Bell M427 helicopter. The primary objective was to use the NRC parameter estimation technique, based on modified maximum likelihood estimation (MMLE), on a limited set of flight test data to efficiently develop an accurate forward-flight mathematical model of the Bell M427. The effect of main rotor design changes on the aircraft stability characteristics was also investigated, using parameter estimation. This program has demonstrated the feasibility of creating a forward-flight rotorcraft aerodynamic mathematical model based on time-domain parameter estimation, and the ability of a 6 degree-of-freedom MMLE model to accurately document the impact of minor rotor modifications on aircraft stability.