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A driveline differential gear housing or diff-case is the heaviest component of a driveline that rotates at high velocities. core shift during diff-case casting is a major source of imbalance as casting cores can never be placed at the exact intended location. Core shift in the present case is defined as combination of pure translation along the parting plane and tilting about two orthogonal axes. Given the ranges of variation of these shift parameters, large numbers of random sampling of these variations are generated through Monte Carlo method where normal distribution of each of the core shift parameters is assumed. Static unbalance values of the diff-case from each of the instances of core shift is calculated using Boolean operation in MSC Adams View and a nonlinear data set is created. Next, a statistical model is created based on a neutral network-based fitting method to appropriately represent the set.

Electronically locking differentials that have dog-clutches may not always have a smooth engagement. The duration of the engagements needs to be quantified, and the different types of engagement need to be qualified. The engagement time is dictated by both the mechanical and electrical sub-systems of the differential. Three different analytical methods were developed to simulate engagement. The first method uses Simulink to co-simulate the electromagnetic behavior of the actuator in ANSYS Maxwell, and the multibody dynamic behavior of the differential in MSC ADAMS. The second method simulates the mechanics of the differential in AMESim, where an equation for the electromagnetic force inside the actuator is integrated into the model. The third method leverages the former two methods by combining the MSC ADAMS multibody dynamic behavior with integrated equation for the electromagnetic force inside the actuator.

Electro-mechanical actuators are widely used in different forms in the automotive industry these days and are very effective in translating rotary motion of the motor to a linear motion with precision as per the requirement. With onset of electric drivelines and other complex driveline configurations, there is an increase in actuator applications. In this study, high fidelity analytical model was developed for a ball ramp clutch actuation system as per the proposed mechanical design and the software controls. The controls architecture is built in SIMULINK environment to drive the plant model of the BLDC motor. Whereas, the entire mechanical system which includes the gear train, ball ramp mechanism, clutch pack stiffness, etc. is modelled in ADAMS tool. The Ball Ramp consists of metal balls positioned in between opposing paired arc-shaped ramp grooves and guided by a cage to keep them equally separated in the same plane.

Overall transmission error (OTE) of gear system has been a main focus of gear dynamics study. The input-output transmission error (TE) depends heavily on mesh phasing conditions. Only reducing loaded transmission error (LTE) of a single gear mesh is not enough to ensure good NVH performance in a multiple gear mesh system. In order to predict OTE during bevel gear design instead of just analyzing single mesh TE, a new bevel gear OTE calculation method will be presented in this study. Based on single mesh parameters including loaded and unloaded TE or mesh stiffness, the OTE of a differential gear set can be calculated without building a complete system model. The effect of phasing on system OTE shows that different tooth combination can have significant effect on dynamic performance which should be considered during design.

A vehicle with automatic transmission is fitted with a parking pawl mechanism to avoid the risk posed by unintended vehicle movement. The system has to be robust enough to function safely even in poor tolerance situations, under extreme temperatures and rigorous durability tests. Thorough study is required in the design and approval of a parking mechanism. Because of the limited research publications in this area, general design practice has been based on heuristic understanding and a build-and-test approach. The combination of physical tests and virtual modeling holds great potential for accelerating and enhancing vehicle development processes. In this paper, an ADAMS model capable of designing, predicting, and optimizing the dynamic characteristics of the parking pawl mechanism is presented. Axiomatic design theory is used to synthesize design solutions in order to satisfy the key requirement of the system.

Paper withdrawn by author.

Cab mounts and suspension bushings are crucial for ride and handling characteristics and must be durable under highly variable loading. Such elastomeric bushings exhibit non-linear behavior, depending on excitation frequency, amplitude and the level of preload. To calculate realistic loads for durability analysis of cars and trucks multi-body simulation (MBS) software is used, but standard bushing models for MBS neglect the amplitude dependent characteristics of elastomers and therefore lead to a trade-off in simulation accuracy. On the other hand, some non-linear model approaches lack an easy to use parameter identification process or need too much input data from experiments. Others exhibit severe drawbacks in computing time, accuracy or even numerical stability under realistic transient or superimposed sinusoidal excitation.

The concept of full vehicle simulation has been embraced by the automobile industry as it is an indispensable tool for analyzing vehicles. Vehicle loads traditionally obtained by road load data acquisition such as wheel forces are typically not invariant as they depend on the vehicle that was used for the measurement. Alternatively, virtual road load data acquisition approach has been adopted in industry to derive invariant loads. Analytical loads prior to building hardware prototypes can shorten development cycles and save costs associated with data acquisition. The approach described herein estimate realistic component load histories with sufficient accuracy and reasonable effort using full vehicle simulations. In this study, a multi-body dynamic model of the vehicle was built and simulated over digitized road using ADAMS software, and output responses were correlated to a physical vehicle that was driven on the same road.