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Superior NVH performance is a key focus in the development of new powertrains. In recent years, computer simulations have gained an increasing role in the design, development, and optimization of powertrain NVH at component and system levels. This paper presents the results of a study carried out on a 4-cylinder in-line spark-ignition engine with focus on growl noise. Growl is a low frequency noise (300-700 Hz) which is primarily perceived at moderate engine speeds (2000-3000 rpm) and light to moderate throttle tip-ins. For this purpose, a coupled and fully flexible multi-body dynamics model of the powertrain was developed. Structural components were reduced using component mode synthesis and used to determine dynamics loads at various engine speeds and loading conditions. A comparative NVH assessment of various crankshaft designs, engine configurations, and in- cylinder gas pressures was carried out.

Taguchi method is a technology to prevent quality problems at early stages of product development and product design. Parameter design method is an important part in Taguchi method which selects the best control factor level combination for the optimization of the robustness of product function against noise factors. The air induction system (AIS) provides clean air to the engine for combustion. The noise radiated from the inlet of the AIS can be of significant importance in reducing vehicle interior noise and tuning the interior sound quality. The porous duct has been introduced into the AIS to reduce the snorkel noise. It helps with both the system layout and isolation by reducing transmitted vibration. A CAE simulation procedure has been developed and validated to predict the snorkel noise of the porous ducted AIS. In this paper, Taguchi's parameter design method was utilized to optimize a porous duct design in an AIS to achieve the best snorkel noise performance.

Weight reduction is very important in automotive design because of stringent demand on fuel economy. Structural optimization of dynamic systems using finite element (FE) analysis plays an important role in reducing weight while simultaneously delivering a product that meets all functional requirements for durability, crash and NVH. With advancing computer technology, the demand for solving large FE models has grown. Optimization is however costly due to repeated full-order analyses. Reanalysis methods can be used in structural vibrations to reduce the analysis cost from repeated eigenvalue analyses for both deterministic and probabilistic problems. Several reanalysis techniques have been introduced over the years including Parametric Reduced Order Modeling (PROM), Combined Approximations (CA) and the Epsilon algorithm, among others.

To improve fuel economy, there is a trend in automotive industry to use light weight, high strength materials. Automotive body structures are composed of several panels which must be downsized to reduce weight. Because this affects NVH (Noise, Vibration and Harshness) performance, engineers are challenged to recover the lost panel stiffness from down-gaging in order to improve the structure borne noise transmitted through the lightweight panels in the frequency range of 100-300 Hz where most of the booming and low medium frequency noise occurs. The loss in performance can be recovered by optimized panel geometry using beading or damping treatment. Topography optimization is a special class of shape optimization for changing sheet metal shapes by introducing beads. A large number of design variables can be handled and the process is easy to setup in commercial codes. However, optimization methods are computationally intensive because of repeated full-order analyses.

A Reliability-Based Design Optimization (RBDO) method for multiple failure regions is presented. The method uses a Probabilistic Re-Analysis (PRRA) approach in conjunction with an approximate global metamodel with local refinements. The latter serves as an indicator to determine the failure and safe regions. PRRA calculates very efficiently the system reliability of a design by performing a single Monte Carlo (MC) simulation. Although PRRA is based on MC simulation, it calculates “smooth” sensitivity derivatives, allowing therefore, the use of a gradient-based optimizer. An “accurate-on-demand” metamodel is used in the PRRA that allows us to handle problems with multiple disjoint failure regions and potentially multiple most-probable points (MPP). The multiple failure regions are identified by using a clustering technique. A maximin “space-filling” sampling technique is used to construct the metamodel. A vibration absorber example highlights the potential of the proposed method.

An approach for Probabilistic Reanalysis (PRA) of a system is presented. PRA calculates very efficiently the system reliability or the average value of an attribute of a design for many probability distributions of the input variables, by performing a single Monte Carlo simulation. In addition, PRA calculates the sensitivity derivatives of the reliability to the parameters of the probability distributions. The approach is useful for analysis problems where reliability bounds need to be calculated because the probability distribution of the input variables is uncertain or for design problems where the design variables are random. The accuracy and efficiency of PRA is demonstrated on vibration analysis of a car and on system reliability-based optimization (RBDO) of an internal combustion engine.

In this paper, the development of random vibration testing schedules for durability design verification of engine mounted products is presented, based on the equivalent fatigue damage concept and the 95th-percentile customer engine usage data for 150,000 miles. Development of the 95th-percentile customer usage profile is first discussed. Following that, the field engine excitation and engine duty cycle definition is introduced. By using a simplified transfer function of a single degree-of-freedom (SDOF) system subjected to a base excitation, the response acceleration and stress PSDs are related to the input excitation in PSD, which is the equivalent fatigue damage concept. Also, the narrow-band fatigue damage spectrum (FDS) is calculated in terms of the input excitation PSD based on the Miner linear damage rule, the Rayleigh statistical distribution for stress amplitude, a material's S-N curve, and the Miles approximate solution.

The advantages of having higher stiffness to weight ratio and strength to weigh ratio that composite materials have resulted in an increased interest in them. In automotive engineering, the weight savings has positive impacts on other attributes like fuel economy and possible noise, vibration and harshness (NVH). The driveline of an automotive system can be a target for possible use of composite materials. The design of the driveshaft of an automotive system is primarily driven by its natural frequency. This paper presents an exact solution for the vibration of a composite driveshaft with intermediate joints. The joint is modeled as a frictionless internal hinge. The Euler-Bernoulli beam theory is used. Lumped masses are placed on each side of the joint to represent the joint mass. Equations of motion are developed using the appropriate boundary conditions and then solved exactly.

In a CAS system, the distance and relative velocity between front and host vehicles are estimated to calculate time-to-collision (TTC). The distance estimates by different methods will certainly include noise which should be removed to ensure the accuracy of TTC calculations. Kalman filter is a good tool to filter such type of noise. Nevertheless, Kalman filter is a model based filter, which means a correct model is important to get the good filtering results. Usually, a vehicle is either moving with a constant velocity (CV) or constant acceleration (CA) maneuvers. This means the distance data between front and host vehicles can be described by either constant velocity or constant acceleration model. In this paper, first, CV and CA models are used to design two Kalman filters and an interacting multiple model (IMM) is used to dynamically combine the outputs from two filters.

A comprehensive formulation is presented for the dynamics of a rotating flexible crankshaft coupled with the dynamics of an engine block through a finite difference elastohydrodynamic main bearing lubrication algorithm. The coupling is based on detailed equilibrium conditions at the bearings. The component mode synthesis is employed for modeling the crankshaft and block dynamic behavior. A specialized algorithm for coupling the rigid and flexible body dynamics of the crankshaft within the framework of the component mode synthesis has been developed. A finite difference lubrication algorithm is used for computing the oil film elastohydrodynamic characteristics. A computationally accurate and efficient mapping algorithm has been developed for transferring information between a high - density computational grid for the elastohydrodynamic bearing solver and a low - density structural grid utilized in computing the crankshaft and block structural dynamic response.

Road-tire induced vibrations are in many vehicles determining the interior noise levels in (semi-) constant speed driving. The understanding of the noise contributions of different connections of the suspension systems to the vehicle is essential in improvement of the isolation capabilities of the suspension- and body-structure. To identify these noise contributions, both the forces acting at the suspension-to-body connections points and the vibro-acoustic transfers from the connection points to the interior microphones are required. In this paper different approaches to identify the forces are compared for their applicability to road noise analysis. First step for the force identification is the full vehicle operational measurement in which target responses (interior noise) and indicator responses (accelerations or other) are measured.

An application of variation simulation for predicting vehicle interior driveline vibration is presented. The model, based on a “Monte Carlo”-style approach, predicts the noise, vibration and harshness (NVH) response of the vehicle driveline based on distributions of imbalance and runout derived from manufacturing production variation (the forcing function) and the vehicle's sensitivity to the forcing function. The model is used to illustrate the change in vehicle interior vibration that results when changes are made to production variation for runout and imbalance of driveline components, and how those same changes result in different responses based on vehicle sensitivity.

The second part of a detailed examination of multivariate correlation of several axle assembly and component parameters to the assembly NVH performance (vibration) measured at the end of the assembly process is presented focusing on the multivariate linear regression analysis. The study is based on test results and measurements acquired from multiple axle assemblies built with the same hypoid gearset, thus effectively eliminating the affect of gearset variation on the test result. Several major components within the axle are considered including the differential housing (that controls wheel differentiation during turns), the axle housing, and several assembly parameters. Details of the multivariate regression include formulation of the linear regression model, model refinements through analysis of subsets of the variables, tests of significance and residual analysis.

The first part of a detailed examination of multivariate correlation of several axle assembly and component parameters to the assembly NVH performance (vibration) measured at the end of the assembly process is presented focusing on preparing the data for multivariate regression analysis. The study is based on test results and measurements acquired from multiple axle assemblies built with the same hypoid gearset, thus effectively eliminating the affect of gearset variation on the test result. Several major components within the axle are considered including the differential housing (that controls wheel differentiation during turns), the axle housing, and several assembly parameters.

The sound quality of a prototype series hydraulic hybrid passenger vehicle powertrain was analyzed. Different sound quality metrics were evaluated to determine which one correlated best with the subjective assessment of sound quality, and a desired sound quality target was developed. Next, the effect of the design of the hydraulic powertrain components on sound quality was analyzed. Two extreme options were analyzed: “stiff” systems with a hard drive shaft or short fluid hoses, and “soft” systems with a soft drive shaft or long fluid hoses. Experimental results from these systems are presented in the paper. Finally, design recommendations were made to achieve the best sound quality of the hybrid hydraulic powertrain, and therefore maximum customer satisfaction.

The air induction system (AIS), which provides clean air to the engine for combustion, is very important for engine acoustics. A practical CAE procedure to predict AIS inlet noise is presented in this paper. GT-Power, a commercially available software program can be used to simulate the engine performance and predict air induction noise. The accuracy of GT-Power is dependent on many variables, such as: proper duct discretization size, proper number of flow splits to model the air box and the capturing of the correct resonator geometry for tuning frequency. Since GT-Power is based on a 1D assumption, several iterations need be performed to model the complex AIS components, such as, irregular shaped air box, resonator volume, porous ducts and perforated pipes. Because of this, the GT-Power AIS model needs to be correlated to test data using transmission loss data.

With the advent of quieter powertrain and improved cabin acoustic sealing, there is an increased focus on noise generated in the HVAC unit and climate control ducting system. With improved insulation from exterior noise sources such as wind & road noise, HVAC noise is more perceptible by the occupants and is a key quality indicator for new generation vehicles. This has increased the use of simulations tools to predict HVAC noise during the virtual development phase of new vehicle programs. With packaging space being premium under the instrument panel, changes to address noise issues are expensive and often impractical. The current methodology includes the best practices in simulation accumulated from prior aero acoustics validation studies on fans, ducts, flaps and plenum volume discharge. The paper details the acoustic noise generation and propagation in the near field downstream of an automotive HVAC unit in conjunction with ducting system.

This paper presents the design of a hybrid powertrain damping control algorithm using the sliding mode control (SMC) scheme. Motor control-based active damping control strategy is used to ensure smooth drive line operation and provide the driver with seamless driving experience. In the case of active damping control, motor and engine speeds are measured to monitor the driveline state, and corrective motor torques are generated to dampen out drive line vibrations. Drive lines are prone to internal vibration (engine, clutches and motors) as well as external disturbances caused by road inputs. As such, fast-response actuator-based damping control systems are desirable in a hybrid powertrain application, where a torque converter is generally not used. The most significant aspect of an active damping control algorithm is the error calculation, based on proper states information, and torque determination based on the adaptive control gain applied to the nonlinear system.

Brake judder is a brake induced vibration that a vehicle driver experiences in the steering wheel or floor panel at highway speeds during vehicle deceleration. The primary cause of this disturbance phenomenon is the brake torque variation (BTV). Virtual CAE tools from both kinematics and compliance standpoints have been applied in analyzing sensitivities of the vehicle systems to BTV. This paper presents a recently developed analytical approach that identifies parameters of steering and suspension systems for achieving optimal settings that desensitize the vehicle response to BTV. The analytical steps of this integrated approach started with creating a lumped mass noise-vibration-harshness (NVH) control model and a separate multi-body dynamics (MBD) suspension model. Then, both models were linked to run in a sequence through optimization software so the results from the MBD model were used as quasi-static inputs to the lumped mass NVH model.

A nonlinear finite element passenger car radial-ply tire model was developed to investigate a tire's three-dimensional transmissibility in the X, Y, and Z directions. The reaction forces of the tire axle in longitudinal (X axis), lateral (Y axis), and vertical (Z axis) directions were recorded when the tire encountered a cleat, and then the FFT (Fast Fourier Transform) algorithm was applied to extract tire's transient response information in the frequency domain. The result showed that this passenger car tire has clear peaks at 47-51 and 91-92 Hz longitudinal, 41-45 Hz lateral, and 80-83Hz vertical. An analytical rigid ring model was also formulated, based on the dynamic equations of the rigid ring tire model. The characteristic equations were obtained and solved for eigenvalues and eigenvectors, which represent tire's free vibration natural frequencies and mode shapes.