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As mass reduction becomes an increasingly important enabler for fuel economy improvement, having a robust structural development process that can comprehend Vehicle Dynamics-specific requirements is correspondingly important. There is a correlation between the stiffness of the body structure and the performance of the vehicle when evaluated for ride and handling. However, an unconstrained approach to body stiffening will result in an overly-massive body structure. In this paper, the authors employ loads generated from simulation of quasi-static and dynamic vehicle events in ADAMS, and exercise structural finite element models to recover displacements and deflected shapes. In doing so, a quantitative basis for considering structural vehicle dynamics requirements can be established early in the design/development process.

Incomplete vehicles are partially manufactured by an Original Equipment Manufacturer (OEM) and subsequently sold to and completed by a final-stage manufacturer. Section S8.8, Final-Stage Manufacturers and Alterers, of Federal Motor Vehicle Safety Standard (FMVSS) 126 states “Vehicle that are manufactured in two or more stages or that are altered (within the meaning of 49 CFR 567.7) after having been previously certified in accordance with Part 567 of this chapter, are not subject to the requirements of S8.1 through S8.5. Instead, all vehicles produced by these manufacturers on or after September 1, 2012, must comply with this standard.” The FMVSS 126 compliance of the completed vehicle can be certified in three ways: by the OEM provided no alterations are made to identified components (TYPE 1), conditionally by the OEM provided the final-stage manufacturer follows specific guidelines (TYPE 2), or by the final-stage manufacturer (TYPE 3).

Recent advancements in simulation software and computational hardware make it realizable to simulate a full vehicle system comprised of multiple sub-models developed in different modeling languages. The so-called, co-simulation allows one to develop a control strategy and evaluate various aspects of a vehicle system, such as fuel efficiency and vehicle drivability, in a cost-effective manner. In order to study the feasibility of the synchronized parallel processing in co-simulation this paper presents two co-simulation frameworks for a complete vehicle system with multiple heterogeneous subsystem models. In the first approach, subsystem models are co-simulated in a serial configuration, and the same sub-models are co-simulated in a parallel configuration in the second approach.

This paper discusses observability of the vehicle states using different sensor configurations as well as fault-tolerant estimation of these states. The optimality of the sensor configurations is assessed through different observability measures and by using a 3-DOF linear vehicle model that incorporates yaw, roll and lateral motions of the vehicle. The most optimal sensor configuration is adopted and an observer is designed to estimate the states of the vehicle handling dynamics. Robustness of the observer against sensor failure is investigated. A fault-tolerant adaptive estimation algorithm is developed to mitigate any possible faults arising from the sensor failures. Effectiveness of the proposed fault-tolerant estimation scheme is demonstrated through numerical analysis and CarSim simulation.

This paper presents the implementation of an off-line optimized torque vectoring controller on an electric-drive vehicle with four in-wheel motors for driver assistance and handling performance enhancement. The controller takes vehicle longitudinal, lateral, and yaw acceleration signals as feedback using the concept of state-derivative feedback control. The objective of the controller is to optimally control the vehicle motion according to the driver commands. Reference signals are first calculated using a driver command interpreter to accurately interpret what the driver intends for the vehicle motion. The controller then adjusts the braking/throttle outputs based on discrepancy between the vehicle response and the interpreter command.

To realize better fuel economy benefits from transmissions, car makers have started the application of torque converter clutch control in second gear and beyond, resulting in greater demand on the torque converter clutch (TCC) and its control system. This paper focuses on one aspect of the control of the torque converter clutch to improve fuel economy and faster response of the transmission. A TCC is implemented to control the slip between the pump and turbine of the torque converter, thereby increasing its energy transfer efficiency and increasing vehicle fuel economy. However, due to the non-linear nature of the torque converter fluid coupling, the slip feedback control has to be very active to handle different driver inputs and road-load conditions, such as different desired slip levels, changes in engine input torques, etc. This non-linearity requires intense calibration efforts to precisely control the clutch slip in all the scenarios.

A system level analysis was carried out on the effect of flow forces on a flow control variable force solenoid (VFS) used in automatic transmissions. Classic flow force model was reviewed as a function of the pressure difference and the solenoid current. A force balance analysis was conducted on the spool valve in the VFS, in order to study the relationship among the control current, flow forces, spring forces, and flow area. Flow bench testing was used to characterize a specific flow control VFS by both the pressure drop and solenoid current, in forward and reverse flow directions. The behavior of flow control VFS valve is significantly affected by flow forces. A sub-system level model was thus created to predict the steady-state and dynamic behavior of the flow VFS valve, which can be used in a transmission system level analysis. The modeling results were compared against experimental data to show the validity of the methodology.

A simulation methodology is developed for the Constant Radius Constant Speed (CRCS) analysis to predict the ISO4138 [1] road test performance. The CRCS analysis can be used to predict the vehicle steady-state handling characteristics such as understeer, rear cornering compliance, and roll gradient, etc. The Yaw-Rate Control methodology is applied to replace the traditional driver-in-the-loop path-following approaches. Comparing to the path-following approaches, the proposed method is simpler to use, more efficient, accurate, and robust.

The imperative to get to the market faster with new and better products, has determined all automotive OEM to rethink their product development cycle, and, as a result, many hardware based processes were replaced and/or augmented with virtual, software based ones. However, the virtualization itself does not guaranties better and faster products. In the area of vehicle dynamics, we concentrate on improving the multi-body model development process, facilitating comprehensive virtual testing, and verifying the robustness of the design. The authors present a highly flexible and efficient environment that encourages, enforces, and facilitates model sharing, reusing of components, and parallelization of vehicle dynamics simulations, developed on top of an existing commercial off-the-shelf engineering software application.

Press hardened steels (PHS) are commonly used in automotive structural applications because of their combination of extremely high strength, load carrying capacity and the ability to form complex shapes in the press hardening process. Recent adoption of increased roof crush standards, side impact requirements and the increased focus on CO2 emissions and mass reduction have led autmotive manufacturers to significantly increase the amount of PHS being designed into future vehicle designs. As a way to further optimize the use of these steels, multi-gauge welded blanks of PHS and multi-material blanks of PHS to microalloyed steels of various thickness have been developed to help achieve these requirements. More recently, tailor rolled PHS, whereby the steel is rolled such that the thickness changes across the width of the sheet, have been developed.

There are generally two types of directional instability that are associated with a vehicle/trailer combination system. The first is typically referred to as static or divergent instability (jack-knifing), which is a common cause of highway accidents. The second can be called dynamic or oscillatory instability (“snaking” or “fish-tailing”). This type of oscillation occurs due to inherently low system damping at higher speeds [1]. It is sensitive to system parameters and operating conditions and may be excited by various disturbances, such as side wind or abrupt steering inputs. Controlling trailer yaw oscillation can be challenging, especially in markets where small passenger cars are commonly used to tow relatively massive trailers at highway speeds with low hitch loads. This study focuses on the second of the two aforementioned types of instability - dynamic or oscillatory instability.

This paper presents a method to reduce the number of occurrences of vehicle deceleration disturbances due to the reduction of regenerative braking in the presence of wheel slip. Usually, regenerative braking is disabled when wheel slip is detected in order to allow the ABS system to efficiently cycle brake pressure. When this happens, the vehicle will momentarily lose deceleration due to the reduction in both regenerative brake torque and friction brake pressure, until friction brake pressure is reapplied. Some ABS activations can be defined as nuisance events, in which full ABS control is not necessary and is exited rapidly; for example, a vehicle driving through a pothole. In these cases it is desirable to continue regenerative braking in order to keep vehicle deceleration as smooth as possible.

This paper proposes a model-based “Cascaded Dual Extended Kalman Filter” (CDEKF) for combined vehicle state estimation, namely, tire vertical forces and parameter identification. A sensitivity analysis is first carried out to recognize the vehicle inertial parameters that have significant effects on tire normal forces. Next, the combined estimation process is separated in two components. The first component is designed to identify the vehicle mass and estimate the longitudinal forces while the second component identifies the location of center of gravity and estimates the tire normal forces. A Dual extended Kalman filter is designed for each component for combined state estimation and parameter identification. Simulation results verify that the proposed method can precisely estimate the tire normal forces and accurately identify the inertial parameters.

This paper presents subjective and objective methods for evaluating transient vehicle dynamics characteristics in four sections: (1) Definition of transient behavior in terms of four traits-agility, stability, precision, and roll support; (2) Description of subjective evaluation methods; (3) Implementation of Design for Six Sigma principles to the development of a steering robot controlled objective test for transient performance; (4) The final section of this paper uses data from simulation and road tests to demonstrate how chassis design parameters can affect transient handling performance.

An air suspension system can consist of many different components. These components include an air compressor, air springs, pneumatic solenoid valves, height sensors, electronic control unit, air reservoir, air lines, pressure sensor, temperature sensor, etc. The system could be designed as a 2-corner rear air suspension or a 4-corner air suspension. In this paper, the pneumatic models of air suspension systems are presented. The suspension system models are implemented in AmeSim. The suspension controls are implemented using Matlab/Simulink. The compressor was modeled using the standard AmeSim element with known mass flow rate as a function of pressure ratio. Air lines were modeled using a friction submodel of pneumatic pipe and control (isolation) valves are modeled using 2 position, 2 port pneumatic servo valves. The air spring is modeled as a single pneumatic chamber, single rod jack with spring assistance to account for spring nonlinearities.

Rubber isolators and bushings are very important components for vehicle performance. However, one often finds it is difficult to get the dynamic properties to be readily used in CAE analysis, either from suppliers or from OEM's own test labs. In this paper, the author provides an analytical method to obtain the dynamic stiffness of an exhaust isolator, using ABAQUS and iSight, with tested or targeted isolator static stiffness information. The analysis contains two steps. The first step is to select the (rubber/EPDM) material properties for the FE isolator model by matching the static stiffness with either the targeted spring rate (linear or nonlinear) or the (tested) load / deflection curve. The second step is to perform dynamic analysis on the statically “validated” FE isolator model to obtain its dynamic properties.