Search Results

This paper presents the final phase of a study to develop the modeling methodology for an advanced steering assembly with a safety-enhanced steering wheel and an adaptive energy absorbing steering column. For passenger cars built before the 1960s, the steering column was designed to control vehicle direction with a simple rigid rod. In severe frontal crashes, this type of design would often be displaced rearward toward the driver due to front-end crush of the vehicle. Consequently, collapsible, detachable, and other energy absorbing steering columns emerged to address this type of kinematics. These safety-enhanced steering columns allow frontal impact energy to be absorbed by collapsing or breaking the steering columns, thus reducing the potential for rearward column movement in severe crashes. Recently, more advanced steering column designs have been developed that can adapt to different crash conditions including crash severity, occupant mass/size, seat position, and seatbelt usage.

In the present study, transfer equations relating the responses of post-mortem human subjects (PMHS) to the mid-sized male Hybrid III test dummy (HIII50) under matched, or nearly-identical, loading conditions were developed via math modeling. Specifically, validated finite element (FE) models of the Ford Human Body Model (FHBM) and the HIII50 were used to generate sets of matched cases (i.e., 256 frontal impact cases involving different impact speeds, severities, and PMHS age). Regression analyses were subsequently performed on the resulting age-dependent FHBM- and HIII50-based responses. This approach was conducted for five different body regions: head, neck, chest, femur, and tibia. All of the resulting regression equations, correlation coefficients, and response ratios (PHMS relative to HIII50) were consistent with the limited available test-based results.

The aluminum alloy 7075-T6 has the potential to be used for structural automotive body components as an alternative to boron steel. Although this alloy shows poor formability at room temperature, it has been demonstrated that hot stamping is a feasible sheet metal process that can be used to overcome the forming issues. Hot stamping is an elevated temperature forming operation in which a hot blank is formed and quenched within a stamping die. Attaining a high quench rate is a critical step of the hot stamping process and corresponds to maximum strength and corrosion resistance. This work looks at measuring the quench rate of AA7075-T6 by way of three different approaches: water, a water-cooled plate, and a bead die. The water-cooled plate and the bead die are laboratory-scale experimental setups designed to replicate the hot stamping/die quenching process.

No two battery cells can be identical. Charging/discharging a battery pack without monitoring cell voltages or SoC (State-of-Charge) will cause cell voltages to deviate over time and the packs useable capacity to decrease quickly. To redistribute charge uniformly among cells, various cell balancing methods have been proposed in the literature. In this paper, a cell balancing method based on a single switched-capacitor is presented from a brand new perspective. Unlike the traditional balancing methods that rely on the voltage divergence criterion, this paper uses the SoC divergence criterion to shuttle charge from a highly charged cell to a poorly charged cell. Moreover, an equivalent resistance of the single-switched capacitor topology is derived in steady state. For fast cell balancing, design guidelines are provided for selecting a proper switching-time period and the capacitor parameters. Ultracapacitors are recommended to achieve this goal.

Aggressive battery usage profiles in electrified vehicle applications require extensive efforts in developing battery management strategy and system design determination to guarantee safe operation under every real-world driving conditions. Experiment based approaches have been widely used for battery system development, but higher costs and longer testing time restrain the number of test cases in the product development process. Battery experiments tend to be conservative to avoid inherent risks of battery failure modes under aggressive battery operation close to the capability limits. Battery Hardware-In-the-Loop (HIL) is an alternative way to overcome the limitations of experiment-based approaches. Battery models in the HIL should provide real-time computation capability and high (at least acceptable) prediction accuracy. Equivalent circuit model (ECM) based HILs have been used owing to their relatively good balance between computational time and prediction accuracy.

A new performance simulation capability has been developed for powersplit HEVs to enable analytical assessment of new engine technologies in the context of HEV system operation and to analyze/understand important system dynamics and control interactions affecting HEV performance. This new capability allows direct simulation with closed-loop controls and the driver, is compatible with Ford standard HEV system simulation capabilities and enables simulation with multiple levels of model fidelity and feature content across the vehicle system. The combined plant Vehicle Model Architecture (VMA) in Simulink was used for the infrastructure. The simulation capability includes a Dymola model of the powersplit transaxle, a Vehicle System Control (VSC) model implemented in Simulink, a high fidelity 2L Atkinson GT-Power engine model, and a simplified representation of the engine controls in Simulink.

Under the initiative of The United States Council for Automotive Research LLC (USCAR) [1], we have developed and run comprehensive friction tests of dual clutch transmission fluids (DCTFs). The focus of this study is to quantify the anti-shudder durability over a simulated oil life of 75,000 shifts. We have evaluated six DCT fluids, including 2 fluids with known field shudder performance. Six different tests were conducted using a DC motor-driven friction test machine (GK test bench): 1. Force Controlled Continuous Slip, 2. Dynamic Friction, 3. Speed controlled Acceleration-Deceleration, 4. Motor-torque controlled Acceleration-Deceleration, 5. Static Friction, and 6. Static Break-Away. The test fluids were aged (with the clutch system) on the test bench to create a realistic aging of the entire friction system simultaneously.

Distance to empty (DTE) estimation is an important factor to electric vehicle (EV) applications due to its limited driving range. The DTE calculation is based on available energy of the battery and power usage by the powertrain components (e.g. electric motor) and climate control components (e.g. PTC heater and electric AC compressor). The conventional way of estimating the DTE is to treat the power consumed by the climate control system the same as the power by the powertrain for either instantaneous or rolling average estimation. The analysis in this study shows that the power consumption by the climate control system should be estimated based on the current ambient conditions and driver's input instead of using the recorded data from the past driving cycles. The climate control should also be considered separately from the powertrain in power usage rolling average calculation, which results in improvements in DTE estimation especially for extreme hot and cold conditions.

There have been many articles published in the last decade or so concerning the components of an electronic stability control (ESC) system, as well as numerous statistical studies that attempt to predict the effectiveness of such systems relative to crash involvement. The literature however is free from papers that discuss how engineers might develop such systems in order to achieve desired steering, handling, and stability performance. This task is complicated by the fact that stability control systems are very complex and their designs and what they can do have changed considerably over the years. These systems also differ from manufacturer to manufacturer and from vehicle to vehicle in a given maker of automobiles. In terms of ESC hardware, differences can include all the components as well as the addition or absence of roll rate sensors or active steering gears to name a few.

The worldwide automotive industry is currently preparing for a market introduction of hydrogen-fueled powertrains. These powertrains in fuel cell electric vehicles (FCEVs) offer many advantages: high efficiency, zero tailpipe emissions, reduced greenhouse gas footprint, and use of domestic and renewable energy sources. To realize these benefits, hydrogen vehicles must be competitive with conventional vehicles with regards to fueling time and vehicle range. A key to maximizing the vehicle's driving range is to ensure that the fueling process achieves a complete fill to the rated Compressed Hydrogen Storage System (CHSS) capacity. An optimal process will safely transfer the maximum amount of hydrogen to the vehicle in the shortest amount of time, while staying within the prescribed pressure, temperature, and density limits. The SAE J2601 light duty vehicle fueling standard has been developed to meet these performance objectives under all practical conditions.

A transportable instrumentation package to collect driver, vehicle and environmental data is described. This system is an improvement on an earlier system and is called TIP-II [13]. Two new modules were designed and added to the original system: a new and improved physiological signal module (PH-M) replaced the original physiological signals module in TIP, and a new hand pressure on steering wheel module (HP-M) was added. This paper reports on exploratory tests with TIP-II. Driving data were collected from ten driver participants. Correlations between On-Board-Diagnostics (OBD), video data, physiological data and specific driver behavior such as lane departure and car following were investigated. Initial analysis suggested that hand pressure, skin conductance level, and respiration rate were key indicators of lane departure lateral displacement and velocity, immediately preceding lane departure; heart rate and inter-beat interval were affected during lane changes.

Downhill tests are widely used as a method of evaluation, development and validation of braking efficiency, friction pair durability, braking balance, as well as fade characteristics and recovery of friction material properties. This test procedure is used for both: passenger vehicles and light & heavy commercial vehicles. The energy levels in the brake system are higher on commercial vehicles and the thermal characteristics much more critical. Added to the fact that such tests are conducted on public highways, it has an intrinsic security risk for both the vehicle tested and all others around. Until a few years ago, it was still feasible to conduct tests downhill on different routes keeping a high security level. Given an increasing traffic on highways, where the test is currently carried out, a need to create a similar downhill procedure (called Guaporé Mountain Test) within a Proving Ground under controlled conditions has been noticed.

During the development of a new friction material, besides the interface between lining/drum is also fundamental take in account all aspects involving the attachment of the linings on the brake shoes. This paper presents an optimization approach to the development and manufacturing parameters of brake linings, applied on medium and heavy duty commercial vehicles, aiming to assure the correct specification of the riveted joint clamp forces. These evaluations were conducted based on the quality tools documents and the theoretical aspects of the product usage as well as the modeling of key elements of the referred mechanism throughout various known applications. A calculation methodology was developed based on brake geometry, its generated forces and braking reactions required for each vehicle family.

With a goal to help develop pressure sensor calibration and deployment algorithms using computer simulations, an Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this research to predict the responses of side crash pressure sensors for unitized vehicles. For occupant protection, acceleration-based crash sensors have been used in the automotive industry to deploy restraint devices when vehicle crashes occur. With improvements in the crash sensor technology, pressure sensors that detect pressure changes in door cavities have been developed recently for vehicle crash safety applications. Instead of using acceleration (or deceleration) in the acceleration-based crash sensors, the pressure sensors utilize pressure change in a door structure to determine the deployment of restraint devices. The crash pulses recorded by the acceleration-based crash sensors usually exhibit high frequency and noisy responses.

In an attempt to assist pressure sensor algorithm and calibration development using computer simulations, an Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this study to predict the responses of side crash pressure sensors for body-on-frame vehicles. Acceleration based, also called G-based, crash sensors have been used extensively to deploy restraint devices, such as airbags, curtain airbags, seatbelt pre-tensioners, and inflatable seatbelts, in vehicle crashes. With advancements in crash sensor technologies, pressure sensors that measure pressure changes in vehicle side doors have been developed recently and their applications in vehicle crash safety are increasing. The pressure sensors are able to detect and record the dynamic pressure change when the volume of a vehicle door changes as a result of a crash.

To better reflect real world driving conditions, the EPA 5-Cycle Fuel Economy method encompasses high vehicle speeds, aggressive vehicle accelerations, climate control system use and cold temperature conditions in addition to the previously used standard City and Highway drive cycles in the estimation of vehicle fuel economy. A standard Powersplit Hybrid Electric Vehicle (HEV) system simulation environment has long been established and widely used within Ford to project fuel economy for the standard EPA City and Highway cycles. Direct modeling and simulation of the complete 5-Cycle fuel economy test set for HEV's presents significant new challenges especially with respect to modeling vehicle thermal management system and interactions with HEV features and system controls. It also requires a structured, systematic approach to validate the key elements of the system models and complete vehicle system simulations.

Engine control unit (ECU) modeling using engine feature C code is an increasingly important part of new vehicle analysis and development tools. The application areas of feature based ECU models are numerous: a) cold vehicle fuel economy (FE) prediction required for recently introduced 5-cycle certification; b) vehicle thermal modeling; c) evaporative (purge) systems design; d) model-in-the-loop/software-in-the-loop (MIL/SIL) vehicle control development and calibration. The modeling method presented in the paper embeds production C-code directly into Simulink at a feature level using an S-Function wrapper. A collection of features critical to accurate engine behavior prediction are compiled individually and integrated according to the newly developed Engine Control Model Architecture (ECMA). Custom MATLAB script based tools enable efficient model construction.

Ford's portfolio approach to sustainable mobility offers a large range of fuel-efficient engines and alternative-fuel vehicles - including EcoBoost®, hybrid, plug-in hybrid, flexible fuel, battery-electric, B20 biodiesel and compressed natural gas or liquefied petroleum gas (CNG/LPG) vehicles. The Ford Fleet Purchase Planner has been developed to assist fleet customers in comparing these alternatives and understanding which vehicles offer the optimal mix to achieve CO₂ emission reductions while balancing corporate financial goals. Vehicle fleets for large corporations can have thousands of vehicles that are replaced on a timescale of months to years. We present the three main components of the Fleet Purchase Planner (patent pending) that provide fleet customers the lowest cost solution to achieving their sustainability goals: the Vehicle Emissions & Fuel Cost Calculator, the Fleet CO₂ Emissions Footprint Status Calculator, and the Purchase Recommender.

Automotive hybrid electric vehicle applications require 1 million (or more) start-stops. This same level of start-stops is also required for hydrogen PEM fuel cell vehicles. In this investigation, a test regime is developed to stress the failure mode of a set of airfoil journal bearings caused by start-stops, and conceive a proper improvement to meet the requirement. Airfoil bearings have been limited by the number of start-stops due to their inherent wearout of coating(s) at low speed. A complete electronic air cathode compressor (electronic supercharger) assembly is tested, employing a pair of φ25 mm journal airfoil bearings. The foils have 34 μm of surface PTFE coating. After 50,000 start-stops, the coating is worn through. Next an improved system is tested, which has modified coating on the bearing journal surfaces. These bearings are examined roughly every 250,000 start-stops. After 1 million start-stops, the coating has worn 5 μm.

Previously, a 10-year-old (YO) pediatric thorax finite element model (FEM) was developed and verified against child chest stiffness data measured from clinical cardiopulmonary resuscitation (CPR). However, the CPR experiments were performed at relatively low speeds, with a maximum loading rate of 250 mm/s. Studies showed that the biomechanical responses of human thorax exhibited rate sensitive characteristics. As such, the studies of dynamic responses of the pediatric thorax FEM are needed. Experimental pediatric cadaver data in frontal pendulum impacts and diagonal belt dynamic loading tests were used for dynamic validation. Thoracic force-deflection curves between test and simulation were compared. Strains predicted by the FEM and the injuries observed in the cadaver tests were also compared for injury assessment and analysis. This study helped to further improve the 10 YO pediatric thorax FEM.