Search Results

The Lane Change Task (LCT) provides a simple, scorable simulation of driving, and serves as a primary task in studies of driver distraction. It is widely accepted, but somewhat limited in functionality, a problem this project partially overcomes. In the Lane Change Task, subjects drive along a road with 3 lanes in the same direction. Periodically, signs appear, indicating in which of the 3 lanes the subject should drive, which changes from sign to sign. The software is plug-and-play for a current Windows computer with a Logitech steering/pedal assembly, even though the software was written 18 years ago. For each timestamp in a trial, the software records the steering wheel angle, speed, and x and y coordinates of the subject. A limitation of the LCT is that few characteristics of this useful software can be readily modified as only the executable code is available (on the ISO 26022 website), not the source code.

Mobility in the automotive and transportation sectors has been experiencing a period of unprecedented evolution. A growing need for efficient, clean and safe mobility has increased momentum toward sustainable technologies in these sectors. Toward this end, battery electric vehicles have drawn keen interest and their market share is expected to grow significantly in the coming years, especially in light-duty applications such as passenger cars. Although the battery electric vehicles feature high performance and zero tailpipe emission characteristics, economic and technical issues such as battery cost, driving range, recharging time and infrastructure remain main hurdles that need to be fully addressed. In particular, the low power density of the battery limits its broad adoption in heavy-duty applications such as class 8 semi-trailer trucks due to the required size and weight of the battery and electric motor.

The article solves the problem of reducing electric power losses of the traction induction machine rotor to prevent its overheating in nominal and high-load modes. Electric losses of the rotor power are optimized by the stabilization of the main magnetic flow of the electric machine at a nominal level with the amplitude-frequency control in a wide range of speeds and increased loads. The quasi-independent excitation of the induction machine allows us to increase the rigidity of mechanical characteristics, decrease the rotor slip at nominal loads and overloads and significantly decrease electrical losses in the rotor as compared to other control methods. The article considers the technology of converting the power of individual phases into a single energy flow using a three-phase electric machine equivalent circuit and obtaining an energy model in the form of equations of instantaneous active and reactive power balance.

In order to improve the steering stability of the dual-motor drive electric vehicle, Taking the yaw rate and the sideslip angle as the control variables, Using the improved two degree of freedom linear dynamic model and seven degree of freedom nonlinear vehicle dynamics model, The hierarchical structure is used to establish the dual-motor drive electric vehicle steering stability control strategy which consist of the upper direct yaw moment decision-making layer based on the sliding mode controller and the lower additional yaw moment distribution layer based on the optimization theory. The Matlab/Simulink-Carsim joint simulation platform was built. The control strategy proposed in this paper was simulated and verified under the snake test condition and double-line shift test condition.

Low voltage hybridization (<60 V) supports engine start/stop, regenerative braking, and constrained torque assist/regeneration at a low cost. This work studies the potential benefits of a novel hybrid system, called a power split supercharger (PSS). A 9 kW motor is shared between boosting the engine or providing hybrid functionalities, allowing it to couple with a small engine and still support good acceleration. However, the PSS operation is limited to only one of the parallel hybrid or boosting modes at each time instance. In this work an equivalent consumption minimization strategy (ECMS) is developed to select the PSS mode and the motor torque during hybrid mode. The PSS operation is simulated over standard EPA drive cycles with an engine mean value model that captures detailed air path and PSS dynamics.

The automotive industry has been witnessing a major shift towards downsized boosted direct injection engines due to diminishing petroleum reserves and increasingly stringent emission targets. Boosted engines operate at a high mean effective pressure (MEP), resulting in higher in-cylinder pressures and temperatures, effectively leading to increased possibility of abnormal combustion events like knock and pre-ignition. Therefore, the compression ratio and boost pressure in modern engines are restricted, which in-turn limits the engine efficiency and power. To mitigate conditions where the engine is prone to knocking, the engine control system uses spark retard and/or mixture enrichment, which decrease indicated work and increase specific fuel consumption. Several researchers have advocated water injection as an approach to replace or supplement existing knock mitigation techniques.

This paper proposes a method to make diagnostic/prognostic judgment about the health of a tire, in term of its wear, using existing on-board sensor signals. The approach focuses on using an estimate of the effective rolling radius (ERR) for individual tires as one of the main diagnostic/prognostic means and it determines if a tire has significant wear and how long it can be safely driven before tire rotation or tire replacement are required. The ERR is determined from the combination of wheel speed sensor (WSS), Global Positioning sensor (GPS), the other motion sensor signals, together with the radius kinematic model of a rolling tire. The ERR estimation fits the relevant signals to a linear model and utilizes the relationship revealed in the magic formula tire model. The ERR can then be related to multiple sources of uncertainties such as the tire inflation pressure, tire loading changes, and tire wear.

Electric Power Assisted Steering (EPAS) is widely adopted in modern vehicles to reduce steering effort. It is probable that some EPAS systems will experience a shutdown due to reliability issues stemming from electrical and/or electronic components. In the event of EPAS failure, power assist becomes unavailable and the steering system reverts to a fully manual state, leading to excessive steering torque demands from the driver to maneuver the vehicle at lower speeds, i.e., under 30 mph. This situation has resulted in dozens of reported crashes and several OEM safety recalls in the past few years. Inspired by recent work which utilizes independent driving torque of in-wheel-motor vehicles to reduce steering torque, this paper proposes the use of Differential Braking Assisted Steering (DBAS) to alleviate steep increases in steering torque upon EPAS failure. DBAS requires software upgrades with minimal hardware modification to EPAS, which is preferable for a backup system.

Brake pad to rotor adhesion following exposure to corrosive environments, commonly referred to as “stiction”, continues to present braking engineers with challenges in predicting issues in early phases of development and in resolution once the condition has been identified. The goal of this study took on two parts - first to explore trends in field stiction data and how testing methods can be adapted to better replicate the vehicle issue at the component level, and second to explore the impacts of various brake pad physical properties variation on stiction propensity via a controlled design of experiments. Part one will involve comparison of various production hardware configurations on component level stiction tests with different levels of prior braking experience to evaluate conditioning effects on stiction breakaway force.

The strong focus on reducing brake drag, driven by a historic ramp-up in global fuel economy and carbon emissions standards, has led to renewed research on brake caliper drag behaviors and how to measure them. However, with the increased knowledge of the range of drag behaviors that a caliper can exhibit comes a particularly vexing problem - how should this complex range of behaviors be represented in the overall road load of the vehicle? What conditions are encountered during coastdown and fuel economy testing, and how should brake drag be measured and represented in these conditions? With the Environmental Protection Agency (amongst other regulating agencies around the world) conducting audit testing, and the requirement that published road load values be repeatable within a specified range during these audits, the importance of answering these questions accurately is elevated. This paper studies these questions, and even offers methodology for addressing them.

Intermediate shaft assembly is used to connect steering gear to the steering wheel. The primary function of the intermediate shaft is to transfer torsional loads. There is a high probability of noise propagating through the Intermediate shaft to the driver. The current standard for measuring the noise is by performing vehicle level subjective evaluations. If improperly clamped at either of the yokes, a sudden change in the direction of the torsional load on the Intermediate shaft can generate a displeasing noise. Noise can also be generated from the constant velocity joint. Intermediate shaft noise can be measured using a microphone or can be correlated to acceleration values. The benefit of measuring the acceleration over sound pressure level is the reduction of complexity of the test environment and test set up. The nature of the noise in question requires the filtering of low frequency data. This paper presents a new test procedure that has been developed by General Motors.

The Chevrolet Volt is an electric vehicle with extended-range that is capable of operation on battery power alone, and on engine power after depletion of the battery charge. First generation Chevrolet Volts were driven over half a billion miles in North America from October 2013 through September 2014, 74% of which were all-electric [1, 12]. For 2016, GM has developed the second-generation of the Volt vehicle and “Voltec” propulsion system. By significantly re-engineering the traction power inverter module (TPIM) for the second-generation Chevrolet Volt extended-range electric vehicle (EREV), we were able to meet all performance targets while maintaining extremely high reliability and environmental robustness. The power switch was re-designed to achieve efficiency targets and meet thermal challenges. A novel cooling approach enables high power density while maintaining a very high overall conversion efficiency.

Side swipe accidents occur primarily when drivers attempt an improper lane change, drift out of lane, or the vehicle loses lateral traction. Past studies of lane change detection have relied on vehicular data, such as steering angle, velocity, and acceleration. In this paper, we use three physiological signals from the driver to detect lane changes before the event actually occurs. These are the electrocardiogram (ECG), galvanic skin response (GSR), and respiration rate (RR) and were determined, in prior studies, to best reflect a driver's response to the driving environment. A novel system is proposed which uses a Granger causality test for feature selection and a neural network for classification. Test results showed that for 30 lane change events and 60 non lane change events in on-the-road driving, a true positive rate of 70% and a false positive rate of 10% was obtained.

Ride control of military vehicles is challenging due to varied terrain and mission requirements such as operating weight. Achieving top speeds on rough terrain is typically considered a key performance parameter, which is always constrained by ride discomfort. Many military vehicles using passive suspensions suffer with compromised performance due to single tuning solution. To further stretch the performance domain to achieving higher speeds on rough roads, semi-active suspensions may offer a wide range of damping possibilities under varying conditions. In this paper, various semi-active control strategies are examined, and improvements have been made, particularly, to the acceleration-driven damper (ADD) strategy to make the approach more robust for varying operating conditions. A seven degrees of freedom ride model and a quarter-car model were developed that were excited by a random road process input modeled using an auto-regressive time series model.

Suspension design is influenced by many factors, especially by vehicle dynamics performance in ride, handling and durability. In the global automotive industry it is common to “customize” or tune suspension parameters so that a vehicle is more acceptable to a different customer base and in a different driving environment. This paper seeks to objectively quantify certain aspects of tuning via ride optimization, taking account of market differences in road surface spectral properties and loading conditions. A computationally efficient methodology for suspension optimization is developed using stochastic techniques. A small (B-class) vehicle is chosen for the study and the following main suspension parameters are selected for optimization - spring stiffness, damping rate and vertical tire stiffness. The road is characterized as a stationary random process, using scaling and shaping filters representative of comparable roads in India and the USA.

Structural stress methods are now widely used in fatigue life assessment of welded structures and structures with stress concentrations. The structural stress concept is based on the assumption of a global stress distribution at critical locations such as weld toes or weld throats, and there are several variants of structural stress approaches available. In this paper, the linear traction stress approach, a nodal force based structural stress approach, is reviewed first. The linear traction stress approach offers a robust procedure for extracting linear traction stress components by post-processing the finite element analysis results at any given hypothetical crack location of interest. Pertinent concepts such as mesh-insensitivity, master S-N curve, fatigue crack initiation and growth mechanisms are also discussed.

Real-time driving simulations are an important tool for verifying vehicle and vehicle component designs with a driver in the loop. They not only provide a cost effective solution but also an ability to verify designs in a safe and controlled operating environment. A real-time driving experiment has been developed for Stryker to compare the ride and handling performance of a baseline passive suspension to that of a Magneto-Rheological (MR) semi-active damper suspension. The Tank Automotive Research Development and Engineering Center (TARDEC) has integrated this new suspension into a real time vehicle dynamics model of the Stryker using the MR suspension model developed by the Original Equipment Manufacturer (OEM). Using this real-time model and the TARDEC Ride Motion Simulator (RMS), TARDEC associates, along with associates from the Stryker Program Management office and the suspension OEM were able to drive and compare the passive and MR Stryker in a virtual environment.

This research paper addresses the ground vehicle reliability prediction process based on a new integrated reliability prediction framework. The integrated stochastic framework combines the computational physics-based predictions with experimental testing information for assessing vehicle reliability. The integrated reliability prediction approach incorporates the following computational steps: i) simulation of stochastic operational environment, ii) vehicle multi-body dynamics analysis, iii) stress prediction in subsystems and components, iv) stochastic progressive damage analysis, and v) component life prediction, including the effects of maintenance and, finally, iv) reliability prediction at component and system level. To solve efficiently and accurately the challenges coming from large-size computational mechanics models and high-dimensional stochastic spaces, a HPC simulation-based approach to the reliability problem was implemented.

The hybrid FEA method combines the conventional FEA method with the energy FEA (EFEA) for computing the structural vibration in vehicle structures when the excitation is applied on the load bearing stiff structural members. Conventional FEA models are employed for modeling the behavior of the stiff members in the vehicle. In order to account for the effect of the flexible members in the FEA analysis, appropriate damping and spring/mass elements are introduced at the connections between stiff and flexible members. Computing properly the values of these damping and spring/mass elements is important for the overall accuracy of the computations. Utilizing in these computations the analytical solutions for the driving point impedance of infinite or semi-infinite members introduces significant approximations.

By adapting vehicle control systems to the skill level of the driver, the overall vehicle active safety provided to the driver can be further enhanced for the existing active vehicle controls, such as ABS, Traction Control, Vehicle Stability Enhancement Systems. As a follow-up to the feasibility study in [1], this paper provides some recent results on data-driven driving skill characterization. In particular, the paper presents an enhancement of discriminant features, the comparison of three different learning algorithms for recognizer design, and the performance enhancement with decision fusion. The paper concludes with the discussions of the experimental results and some of the future work.