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An aerodynamic analysis methodology which makes efficient use of ANSA and FLUENT software's in the aerodynamic design of tractor-trailer class heavy commercial road vehicles is presented. The aerodynamic drag coefficient of the truck is used as the main control parameter to evaluate the performance of the methodology. Analysis methodology development activities include determining optimal FLUENT software analysis parameters for the defined problem (RANS based turbulence models, wall boundary layer models, solution schemes) and the necessary ANSA mesh generation parameters (boundary layer number and growth rate, wall surface mesh resolution, total mesh resolution). Proposed methodology is first constructed based on CFD simulations for the zero-degree yaw angle case of the 1/8 sized GCM geometry. The present results are within 1% of the experimental data.

This paper reviews the correlation concepts and tools available, with the emphasis on their historical origins, mathematical properties and applications. Two of the most commonly used statistical correlation indicators, i.e., modal assurance criterion (MAC) for structural deformation pattern identification/correlation and the coefficient of determination (R2) for data correlation are investigated. The mathematical structure of R2 is critically examined, and the physical meanings and their implications are discussed. Based on the insights gained from these analyses, a data scatter measure and a dependency measure are proposed. The applications of the measures for both linear and nonlinear data are also discussed. Finally, several worked examples in vehicle dynamics analysis and statistical data analyses are provided to demonstrate the effectiveness of these concepts.

The 2014 SAE Buckendale Lecture will address the past developments and challenges of electromechanical “smart” systems for improving commercial vehicles' functionality. Electromechanical systems combine traditional mechanical devices with electrical components to provide far higher degree of functionality and adaptability for improved vehicle performance. The significant advances in microprocessors and their widespread use in consumer products have promoted their implementation in various classes of vehicles, resulting in “smart” devices that can sense their operating environment and command an appropriate action for improved handling, stability, and comfort. The chassis and suspension application of electromechanical devices mostly relate to controllable suspensions and vehicle dynamic management systems, such as Electronic Stability Control.

This study presents a practical theoretical method to judge the aerodynamic response of buses in the early design stage based on both aerodynamic and design parameters. A constant longitudinal velocity 2-DOF vehicle lateral dynamics model is used to investigate the lateral response of a bus under nine different wind gusts excitations. An appropriate 3-D CFD simulation model of the bus shape results is integrated with carefully chosen design parameters data of a real bus chassis and body to obtain vehicle lateral dynamic response to the prescribed excitations. Vehicle model validity is carried out then, the 2-DOF vehicle lateral dynamics model has been executed in MATLAB Simulink environment with the selected data. Simulation represents the vehicle in a straight ahead path then entered a gusting wind section of the track with a fixed steering wheel. Vehicle response includes lateral deviation (LD), lateral acceleration (LA), yaw angle (YA) and yaw rate (YR).

The Continuously Variable Transmission (CVT) is a widely adopted transmission system. The operation of a CVT is simple, but successfully foretelling the longitudinal motion of a vehicle that utilizes this transmission is sophisticated. As a result, different vehicles taking part in BAJA-SAE competitions were developed using various strategies to model the vehicle’s longitudinal dynamics and CVT operation. This article aims to provide a tool for obtaining a quantitative estimate of the longitudinal performance of a CVT equipped vehicle and for the selection of an optimal drive-train gear ratio for such a vehicle. To this end, this article proposes a novel, relatively simple, and reasonably accurate mathematical approach for modeling the longitudinal motion of a vehicle utilizing a CVT, which was developed by a novel integration of existing vehicle dynamics concepts.

The automotive world has seen an increase in customer demands for vehicles having low noise and vibrations. One of the most important source of noise and vibrations associated with vehicles is the vibration of driveline systems. For commercial vehicles, the refinement of drivelines from NVH point of view is complex due to the cost and efficiency constraints. The typical rear wheel drive configuration of commercial vehicles mostly amplifies the torsional vibrations produced by engine which results into higher noise in the vehicle operating speed range. Theoretically, there are various options available for fine tuning the torsional vibration performance of the vehicle drive train. The mass moments of inertia and stiffness of the drivetrain components play significant role in torsional vibration damping, however, except minor changes to flywheel mass, it is hardly possible to change other components, subject to design limitations.

In last few years there has been great research to increase safety of on-road vehicles by providing information of various vehicle parameters to the user/driver while driving on road. Many algorithms have been developed to assess the vehicle run time situations and enable vehicle ECU to take decisions for autonomous driving. These algorithms are derived using data captured from sensors predominantly make use of vehicle dynamic information. The design proposed in this paper discusses capturing of two important and critical vehicle run time parameters i.) Vehicle tire pressure and the ii.) Road gradient. These parameters then help us in determining the effective fuel efficiency of the vehicle and approximate distance that user can drive with the amount of fuel remaining in the tank.

This paper presents the test track scenario design and analysis used to estimate the performances of heavy vehicles equipped with forward collision warning and automatic emergency braking systems in rear-end crash scenarios. The first part of this design and analysis study was to develop parameters for brake inputs in test track scenarios simulating a driver that has insufficiently applied the brakes to avoid a rear-end collision. In the second part of this study, the deceleration limits imposed by heavy vehicles mechanics and brake systems are used to estimate automatic emergency braking performance benefits with respect to minimum stopping distance requirements set by Federal Motor Vehicle Safety Standards. The results of this study were used to complete the test track procedures and show that all heavy vehicles meeting regulatory stopping distance requirements have the braking capacity to demonstrate rear-end crash avoidance improvements in the developed tests.

The joint forces and moments applied to the joints in an air suspension system in truck are important input loads for lightweight and fatigue analysis of bushings, air spring brackets, torque arms and trailing arms. In order to derive a reliable solution of joint forces and moments, engineers will generally use Multi Body Dynamics (MBD) simulation software, like ADAMS, which can save time in product development cycle. Taking an air suspension in truck as a study example, a 2-dimensional quasi-static model of an air suspension, whose stiffness of air spring and bushing is nonlinear, is established in ADAMS environment. After that, simulations are performed at the typical and extreme working condition respectively, and the results are compared with another three cases. Case I assumes that the stiffness of air spring is linear but the stiffness of bushings, including torsion and radial stiffness, are nonlinear.

Vehicle suspension is a critical system which influences vehicle stability, ride comfort and finally the performance of the car. Designing a good suspension will positively influence the customer perception of the ride comfort and handling of the vehicle. In the present scenario, large electrification drive across the globe in the automotive sector are encouraging the manufacturers to explore the possibility of replacing the engine with the electric motor and battery in a conventional vehicle. Dynamic characteristics of the vehicle may vary due to change in mass distribution and center of gravity of the vehicle, which in turn will have an impact on the suspension characteristics. To avoid the negative impact on the ride and handling, suspension characteristics like pitch, bounce, roll, wheel rate, camber angle, toe in/out need to be reassessed and modified. They are likely to impact suspension geometry and vehicle stability during maneuvers involving oversteer and understeer.

Front suspension frame is an integral part of automobile chassis which acts as a major load carrying structural member and connects different suspension components with body. It provides the required stiffness for achieving desired vehicle dynamics performance. Acting as a major road load path from tire to body, it also acts as a mounting base for suspension arm, steering and compression rod. Considering the competitive market conditions, increased fuel efficiency demand along with enhanced structural durability, it is important to evaluate suspension frame for stiffness and durability using Computer Aided Engineering (CAE) methodology so as to reduce product development time and First Time Right cost effective design. In this paper focus is given on CAE methodology used to design a light weight tubular kind of suspension frame for light commercial vehicle with stiffness comparable to conventional sheet metal suspension frame and similar durability performance with reduced weight.

Rollover has for long been a major safety concern for trucks, and will be even more so as automated driving is envisaged to becoming a key element of future mobility. A natural way to address rollover is to extend the capabilities of current active-safety systems with a system that intervenes by steering or braking actuation when there is a risk of rollover. Assessing and predicting the rollover is usually performed using rollover indices calculated either from lateral acceleration or lateral load transfer. Since these indices are evaluated based on different physical observations it is not obvious how they can be compared or how well they reflect rollover events in different situations. In this paper we investigate the implication of the above mentioned rollover indices in different critical maneuvers for a heavy 8×4 twin-steer truck.

This study investigates the self-adjusted cutting parameter technique to improve the drilling of multi-stacked material. The technique consists in changing the cutting strategy automatically, according to the material being machined. The success of this technique relies on an accurate signal analysis, whatever the process setting. Motor current or thrust force are mostly used as incoming signals. Today, analyses are based on the thresholding method. This consists in assigning lower and upper limits for each type of material. The material is then identified when the signal level is stabilized in between one of the thresholds. Good results are observed as long as signal steps are significantly distinct. This is the case when drilling TA6V-CFRP stacks. However, thrust force level remains roughly unchanged for AA7175-CFRP stacks, leading to overlapping thresholds. These boundary limits may also change with tool geometry, wear condition, cutting parameters, etc.

Temporal changes of the onset flow field during on-road driving events, such as overtaking and passing, causes a complex interaction between aerodynamics of two vehicles. This can affect vehicle dynamics as well as steering input from the driver. In extreme situations this can cause a risk to driving comfort and safety. In order to optimize the shape of a vehicle, a fundamental understanding of the underlying pressure distribution during these scenarios is necessary. This paper describes the experimental method to measure the surface pressure and vehicle motion during overtaking a vehicle and passing a vehicle on a proving ground. Two primary vehicles, a C-Hatchback and a B-Crossover, were instrumented and a medium sized van and a 3.5 t truck were used as secondary vehicles without instrumentation. The highly asymmetric pressure distribution acting on the primary vehicles during the driving events is characterized using a simplified illustration method.

We have recently obtained experimental data and used them to develop computational models to quantify occupant impact responses and injury risks for military vehicles during frontal crashes. The number of experimental tests and model runs are however, relatively small due to their high cost. While this is true across the auto industry, it is particularly critical for the Army and other government agencies operating under tight budget constraints. In this study we investigate through statistical simulations how the injury risk varies if a large number of experimental tests were conducted. We show that the injury risk distribution is skewed to the right implying that, although most physical tests result in a small injury risk, there are occasional physical tests for which the injury risk is extremely large. We compute the probabilities of such events and use them to identify optimum design conditions to minimize such probabilities.

In this paper, a gain-scheduling optimal control approach is proposed to enhance yaw stability of articulated commercial vehicles through active braking of the proper wheel(s). For this purpose, an optimal feedback control is used to design a family of yaw moment controllers considering a broad range of vehicle velocities. The yaw moment controller is designed such that the instantaneous tractor yaw rate and articulation angle responses are forced to track the target values at each specific vehicle velocity. A gain scheduling mechanism is subsequently constructed via interpolations among the controllers. Furthermore, yaw moments derived from the proposed controller are realized by braking torque distribution among the appropriate wheels. The effectiveness of the proposed yaw stability control scheme is evaluated through software-in-the-loop (SIL) co-simulations involving Matlab/Simulink and TruckSim under lane change maneuvers.

In this paper the influence of different turbulent flow conditions on the aerodynamic drag of a quarter scale model with notchback and estate back rear ends is investigated. FKFS swing® (Side Wind Generator) is used to generate a turbulent flow field in the test section of the IVK model scale wind tunnel. In order to investigate the increase in drag with increasing yaw, a steady state yaw sweep is performed for both vehicle models. The shape of the drag curves vary for each vehicle model. The notchback model shows a more pronounced drag minimum at 0° yaw angle and experiences a more severe increase in drag at increasing yaw when compared to the estate back model. Unsteady time averaged aerodynamic drag values are obtained at two flow situations with different turbulent length scales, turbulence intensities, and yaw angle amplitudes. While the first one is representing light wind, the second one is recreating the presence of strong gusty wind.

In vehicle dynamics modelling, the road profile is generally treated in one of two ways; either the gradient is a property that changes over a length scale far greater than that of the vehicle's wheelbase, or as a very detailed road surface model for determining the behaviour of vehicle suspensions. Occasionally, for modelling the behaviour of off-road vehicles, step-climbing manoeuvres are modelled. We propose an extension of these step-climbing models to a general, continuously varying road gradient model for cases where the distance over which the large gradient change occurs are of similar length-scale as the vehicle wheelbase. The motivation behind this work comes from a road gradient and vehicle mass estimation problem where it was noticed that very sudden gradient changes have a significant impact on the powertrain, but in a way that is not proportional to the attitude change of the vehicle.

As the cost and complexity of modern aircraft systems increases, emphasis has been placed on model-based design as a means for reducing development cost and optimizing performance. To facilitate this, an appropriate modeling environment is required that allows developers to rapidly explore a wider design space than can cost effectively be considered through hardware construction and testing. This wide design space can then yield solutions that are far more energy efficient than previous generation designs. In addition, non-intuitive cross-coupled subsystem behavior can also be explored to ensure integrated system stability prior to hardware fabrication and testing. In recent years, optimization of control strategies between coupled subsystems has necessitated the understanding of the integrated system dynamics.

The way to autonomous driving is closely connected to the capability of verifying and validating Advanced Driver Assistance Systems (ADAS), as it is one of the main challenges to achieve secure, reliable and thereby socially accepted self-driving cars. Hardware-in-the-Loop (HiL) based testing methods offer the great advantage of validating components and systems in an early stage of the development cycle, and they are established in automotive industry. When validating ADAS using HiL test benches, engineers face different barriers and conceptual difficulties: How to pipe simulated signals into multiple sensors including radar, ultrasonic, video, or lidar? How to combine classical physical simulations, e.g. vehicle dynamics, with sophisticated three-dimensional, GPU-based environmental simulations? In this article, we present current approaches of how to master these challenges and provide guidance by showing the advantages and drawbacks of each approach.