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Connected autonomy brings with it the means of significantly increasing vehicle Energy Economy (EE) through optimal Eco-Driving control. Much research has been conducted in the area of autonomous Eco-Driving control via various methods. Generally, proposed algorithms fall into the broad categories of rules-based controls, optimal controls, and meta-heuristics. Proposed algorithms also vary in cost function type with the 2-norm of acceleration being common. In a previous study the authors classified and implemented commonly represented methods from the literature using real-world data. Results from the study showed a tradeoff between EE improvement and run-time and that the best overall performers were meta-heuristics. Results also showed that cost functions sensitive to the 1-norm of acceleration led to better performance than those which directly minimize the 2-norm.

In the current work, unidirectional (UD) carbon fiber composite hatsection component with two different layups are studied under dynamic three-point bending loading. The experiments are performed at various impact velocities, and the effects of impactor velocity and layup on acceleration histories are compared. A macro model is established with LS-DYNA for a more detailed study. The simulation results show that the delamination plays an important role during dynamic three-point bending test. Based on the analysis with a high-speed camera, the sidewall of hatsection shows significant buckling rather than failure. Without considering the delamination, the current material model cannot capture the post-failure phenomenon correctly. The sidewall delamination is modeled by assumption of larger failure strain together with slim parameters, and the simulation results of different impact velocities and layups match the experimental results reasonably well.

Charge boosting strategy plays an essential role in improving the power density of diesel engines while meeting stringent emissions regulations. In downsized two-stage turbocharged engines, turbocharger matching is critical to achieve desired boost pressure while maintaining sufficiently fast transient response. A numerical simulation model is developed to evaluate the effect of two-stage turbocharger configurations on the perceived vehicle acceleration. The simulation model developed in GT-SUITE consists of engine, drivetrain, and vehicle dynamics sub-models. A model-based turbocharger control logic is developed in MATLAB using an analytical compressor model and a mean-value engine model. The components of the two-stage turbocharging system evaluated in this study include a variable geometry turbine in the high-pressure stage, a compressor bypass valve in the low-pressure stage and an electrically assisted turbocharger in the low-pressure stage.

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.

This study was conducted to develop and validate a multidimensional measure of shift quality as perceived by drivers during kick-down shift events for automatic transmission vehicles. As part of the first study, a survey was conducted among common drivers to identify primary factors used to describe subjective gear-shifting qualities. A factor analysis on the survey data revealed four semantic subdimensions. These subdimensions include responsiveness, smoothness, unperceivable, and strength. Based on the four descriptive terms, a measure with semantic scales on each subdimension was developed and used in an experiment as the second study. Twelve participants drove and evaluated five vehicles with different gear shifting patterns. Participants were asked to make kick-down events with two different driving intentions (mild vs. sporty) across three different speeds on actual roadway (local streets and highway).

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.

Fuel cell based powertrains are considered as potential candidates for future vehicles. Modeling of vehicle powertrains, using a combination of components and energy storage media, are widely used to predict vehicle performances under different duty cycles. This paper deals with performance analysis of a light-duty vehicle comprised of a PEM fuel cell stack, in combination with different energy storage systems using Powertrain Simulation Analysis Toolkit (PSAT). The performance of the stack was characterized by experimental data on a smaller PEM stack and was used in the simulation. The stack data was collected at controlled loading and thermal parameters. Three energy storage systems are considered in the analysis: nickel metal hydride battery storage, lithium-ion battery storage and ultra capacitor energy storage. The simulation results were analyzed for comparative evaluations and to optimize the performance of the fuel cell powertrain configurations.

Two soft-sensing methods which are neural network and Kalman filter for estimating vehicle side slip angle are compared. A radial basis function (RBF) neural network based soft-sensing model is proposed to estimate vehicle side slip angle in driver-vehicle closed-loop system. Vehicle side slip angle is considered as mapping of time series of yaw rate and lateral acceleration which are easily measured, the nonlinear mapping relationship of the three state parameters is established through neural network. In addition the method based on Kalman filter is also given. The results of comparison between estimation and measurement show that the neural network method proposed in this paper has higher accuracy and less computation requirement. It can provide theoretical guidance for design of estimator in vehicle stability control system.

Most current applications of digital human figure models for ergonomic assessments of manual tasks focus on the analysis of a static posture. Tools available for static analysis include joint-specific strength, calculation of joint moments, balance maintenance capability, and low-back compression or shear force estimates. Yet, for many tasks, the inertial loads due to acceleration of body segments or external objects may contribute significantly to internal body forces and tissue stresses. Due to the complexity of incorporating the dynamics of motion into analysis, most commercial software packages used for ergonomic assessment do not have the capacity to include dynamic effects. Thus, commercial human modeling packages rarely provide an opportunity for the user to determine if a static analysis is sufficient.

In order to develop confidence in numerical models which are used for automotive crash simulations, results are compared with test data. Modeling assumptions are made when constructing a simulation model for a complex system, such as a vehicle. Through a thorough understanding of the modeling assumptions an appropriate set of variables can be selected and adjusted in order to improve correlation with test data. Such a process can lead to better modeling practices when constructing a simulation model. Comparisons between the time history of acceleration responses from test and simulations are the most challenging. Computing accelerations correctly is more difficult compared to computing displacements, velocities, or intrusion levels due to the second order differentiation with time. In this paper a methodology for enabling the update of a simulation model for improved correlation is presented.

Automated clutches for vehicle startup is being increasingly deployed in commercial trucks for benefits, which include driver comfort, gradient performance, improved clutch life, emissions and driveline vibration reduction potential. The process of designing the controller is divided into 2 parts. Firstly, the parameter estimation of previously developed driveline models is carried out. The procedure involves an off-line minimization technique based on measured and estimated speeds. Secondly, the nominal plant model is used to develop LQR based optimal control strategy, which takes into account the slip time, dissipated power and slip acceleration. Mathematical expression of the performance index is clearly developed. A variety of clutch lock up profiles can be incorporated by changing a single tuning parameter, thus providing the driver the ability to select a launch profile based on specific driving objectives.

The sophistication of all-wheel-drive technology is approaching the point where the drive torque to each wheel can be independently controlled. This potentially offers vehicle handling enhancements similar to those provided by Dynamic Stability Control, but without the inevitable reduction in vehicle acceleration. Independent control of all-wheel-drive torque distribution would therefore be especially beneficial under acceleration close to the limit of stability. A vehicle model of a typical sports sedan was developed in Simulink, with fully independent control of torque distribution. Box-Behnken experimental design was employed to determine which torque distribution parameters have the greatest impact on the vehicle course and acceleration. A proportional-integral control strategy was implemented, applying yaw rate feedback to vary the front-rear torque distribution, and lateral acceleration feedback to adjust the left-right distribution.

This paper describes the rattle mechanisms that exist in seat belt retractors and the vehicle acceleration conditions that induce these responses. Three principal sources of rattle include: 1) the sensor, 2) the spool, and 3) the lock pawl. In-vehicle acceleration measurements are used to characterize retractor excitation and are subsequently employed for laboratory testing of retractor rattle. The merits and demerits of two testing methods, based on frequency domain and time domain shaker control, are discussed.

The loudness of powertrain noise generally increases with increasing rpm. In the case of ‘linear’ powertrain acceleration sound, the loudness versus time relationship is well described by a linear function. Two studies were conducted on powertrain linearity. The first used tests of similarity and preference to determine whether subjects could detect changes in linearity. The second used a subjective test of preference to investigate how subjects' preference varied with differing degrees of linearity. In both studies, stimulus sets were created by artificially introducing a controlled degree of non-linearity into a nominally linear powertrain sound. The results of the first study indicate that linearity is a phenomenon that naive subjects can readily detect, and that it has an effect on overall preference. Furthermore, the second study shows that preference is related to the magnitude and position of nonlinearities in the growth of loudness versus time during an acceleration run.

The effects of stress in brain material was investigated with experimental and computational idealizations of the head. A water-filled cylinder impacted by a free traveling mass serves to give insight into what could happen to the brain during impact. Under an impact of sufficient velocity, cavitation can occur on the cylinder boundary opposite impact. Limited internal vaporization of the fluid may also occur during severe impact events. Cavitation occurred in these experiments at accelerations greater than 150 g's. Head forms of different sizing will experience an acceleration magnitude inversely proportional to the size difference to produce a similar pressure/cavitation response.

Properties of the human neck which may influence a person's susceptibility to “whiplash” injury during lateral impact have been studied in 96 normal subjects. Subjects were chosen on the basis of age, sex, and stature and data were grouped into six primary categories based on sex (F, M) and age (18-24, 35-44, 62-74). The data include: measures of head, neck and body anthropometry in standing and simulated automotive seating positions, three-dimensional range of motion of the head and neck, head/neck response to low-level acceleration, and both stretch reflex time and voluntary isometric muscle force in the lateral direction. Reflex times are found to vary from about 30 to 70 ms with young and middle aged persons having faster times than older persons, and females having faster times than males. Muscle strength decreases with age and males are, on the average, stronger than females.