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This research was to model a 6×4 tractor-trailer rig using TruckSim and simulate severe braking maneuvers with hardware in the loop and software in the loop simulations. For the hardware in the loop simulation (HIL), the tractor model was integrated with a 4s4m anti-lock braking system (ABS) and straight line braking tests were conducted. In developing the model, over 100 vehicle parameters were acquired from a real production tractor and entered into TruckSim. For the HIL simulation, the hardware consisted of a 4s4m ABS braking system with six brake chambers, four modulators, a treadle and an electronic control unit (ECU). A dSPACE simulator was used as the “interface” between the TruckSim computer model and the hardware.

A variety of methodologies to use embedded multicore controllers efficiently has been discussed in the last years. Several assumptions are usually made in the automotive domain, such as static assignment of tasks to the cores. This paper shows an approach for efficient task allocation depending on different system modes. An engine management system (EMS) is used as application example, and the performance improvement compared to static allocation is assessed. The paper is structured as follows: First the control algorithms for the EMS will be classified according to operating modes. The classified algorithms will be allocated to the cores, depending on the operating mode. We identify mode transition points, allowing a reliable switch without neglecting timing requirements. As a next step, it will be shown that a load distribution by mode-dependent task allocation would be better balanced than a static task allocation.

As the original engine sound is usually not enough to satisfy the driver’s desire for a sporty and fascinating sound, Active Noise Control (ANC) and Active Sound Design (ASD) have been great technologies in automobiles for a long time. However, these technologies which enhance the sound of vehicles using loud speakers or electromagnetic actuators etc. lead to the increase of cost and weight due to the use of external amplifiers or actuators. This paper presents a new technology for generating a target sound by the active control of a permanent magnet synchronous motor (PMSM) of a mass-production steering system. The existing steering hardware or motor is not changed, but only additional software is added. Firstly, an algorithm of this technology, called Active Sound Generation (ASG), is introduced which is compiled and included in the ECU target code. Then the high frequency noise issue and its countermeasures are presented.

It is essential to include uncertainties in the simulation process in order to perform reliable vibroacoustic predictions in the early design phase. In this contribution, uncertainties are quantified using the generalized Polynomial Chaos (gPC) expansion in combination with a Finite Element (FE) model of a vehicle body in white. It is the objective to particularly investigate the applicability of the gPC method in the industrial context with a high number of uncertain parameters and computationally expensive models. A non-intrusive gPC expansion of first and second order is implemented and the approximation of a stochastic response process is compared to a Latin Hypercube sampling based reference solution with special regard to accuracy and computational efficiency. Furthermore, the method is examined for other input distributions and transferred to another FE model in order to verify the applicability of the gPC method in practical applications.

During the last decades, big steps have been taken towards a realistic simulation of NVH (Noise Vibration Harshness) behavior of vehicles using the Finite Element (FE) method. The quality of these computation models has been substantially increased and the accessible frequency range has been widened. Nevertheless, to perform a reliable prediction of the vehicle vibroacoustic behavior, the consideration of uncertainties is crucial. With this approach there are many challenges on the way to valid and useful simulation models and they can be divided into three areas: the input uncertainties, the propagation of uncertainties through the FE model and finally the statistical output quantities. Each of them must be investigated to choose sufficient methods for a valid and fast prediction of vehicle body vibroacoustics. It can be shown by rough estimation that dimensionality of the corresponding random space for different types of uncertainty is tremendously high.

This paper describes a novel approach for modeling an automotive HVAC unit. The model consists of black-box models trained with experimental data from a self-developed measurement setup. It is capable of predicting the temperature and mass flow of the air entering the vehicle cabin at the various air vents. A combination of temperature and velocity sensors is the basis of the measurement setup. A measurement fault analysis is conducted to validate the accuracy of the measurement system. As the data collection is done under fluctuating ambient conditions, a review of the impact of various ambient conditions on the HVAC unit is performed. Correction models that account for the different ambient conditions incorporate these results. Numerous types of black-box models are compared to identify the best-suited type for this approach. Moreover, the accuracy of the model is validated using test drive data.

Highly automated driving (HAD) is under rapid development and will be available for customers within the next years. However the evidence that HAD is at least as safe as human driving has still not been produced. The challenge is to drive hundreds of millions of test kilometers without incidents to show that statistically HAD is significantly safer. One approach is to let a HAD function run in parallel with human drivers in customer cars to utilize a fraction of the billions of kilometers driven every year. To guarantee safety, the function under test (FUT) has access to sensors but its output is not executed, which results in an open loop problem. To overcome this shortcoming, the proposed method consists of four steps to close the loop for the FUT. First, sensor data from real driving scenarios is fused in a world model and enhanced by incorporating future time steps into original measurements.

In order to extend the operability limit of the gasoline compression ignition (GCI) engine, as an avenue for low temperature combustion (LTC) regime, the effects of parametric variations of engine operating conditions on the performance of six-stroke GCI (6S-GCI) engine cycle are numerically investigated, using an in-house 3D CFD code coupled with high-fidelity physical sub-models along with the Chemkin library. The combustion and emissions were calculated using a skeletal chemical kinetics mechanism for a 14-component gasoline surrogate fuel. Authors’ previous study highlighted the effects of the variation of injection timing and split ratio on the overall performance of 6S-GCI engine and the unique mixing-controlled burning mode of the charge mixtures during the two additional strokes. As a continuing effort, the present study details the parametric studies of initial gas temperature, boost pressure, fuel injection pressure, compression ratio, and EGR ratio.

In the last decades the development time of vehicles has been drastically reduced due to the application of advanced numerical and experimental methods. Specifications concerning durability and other functional attributes for every new model improve for every vehicle. In particular, for machines and components under variable multiaxial loading, fatigue evaluation is one of the most important steps in the design process. Appropriate material testing and simulation is the key to efficient life prediction. However, the life of automotive components, power plants and other high-temperature facilities depends mostly on thermo-mechanical fatigue (TMF). This is due to the normally variable service conditions, which contain the phases of startup, full load, partial load and shut-down.

The need of weight reduction for fuel reduction and CO₂ regulations enforces the use of light-weight materials for structural parts also. The importance of reinforced composites will grow in this area. While the structural behavior and the simulation up to high strain-rate processes for those materials have been in the focus of investigation for many years, nowadays the simulation of high cycle fatigue behavior is getting important as well. Efficient fatigue analysis for metals was developed by understanding the microscopic behavior (crack nucleation and initiation) and bringing it to the macroscopic level by combining it with the matching test data (SN curves, etc.). Similar approaches can be applied to composite materials as well.

This paper presents four methodologies for modeling gear mesh excitations in simple and compound planetary gear sets. The gear mesh excitations use simplified representations of the gear mesh contact phenomenon so that they can be implemented in a numerically efficient manner. This allows the gear mesh excitations to be included in transmission system-level, multibody dynamic models for the assessment of operating noise and vibration levels. After presenting the four approaches, a description is made regarding how they have been implemented in software. Finally, example models are used to do a comparison between the methods

In the present work we investigated experimentally and computationally the unsteady flow around a BMW car model including wheels*. This simulation yields mean flow and turbulence fields, enabling the study aerodynamic coefficients (drag and lift coefficients, three-dimensional/spatial wall-pressure distribution) as well as some unsteady flow phenomena in the car wake (analysis of the vortex shedding frequency). Comparisons with experimental findings are presented. The computational approach used is based on solving the complete transient Reynolds-Averaged Navier-Stokes (TRANS) equations. Special attention is devoted to turbulence modelling and the near-wall treatment of turbulence. The flow calculations were performed using a robust, eddy-viscosity-based ζ - ƒ turbulence model in the framework of the elliptic relaxation concept and in conjunction with the universal wall treatment, combining integration up to the wall and wall functions.

Supervisory control strategy of a hybrid electric vehicle (HEV) provides target powers and operating points of an internal combustion engine and an electric motor. To promise efficient driving of the HEV, it is needed to find the proper values of control parameters which are used in the strategy. However, it is very difficult to find the optimal values of the parameters by doing experimental tests, since there are plural parameters which have dependent relationship between each other. Furthermore variation of the test results makes it difficult to extract the effect of a specific parameter change. In this study, a model based parameter optimization method is introduced. A vehicle simulation model having the most of dynamics related to fuel consumption was developed and validated with various experimental data from real vehicles. And then, the supervisory control logic including the control parameters was connected to the vehicle model.

A vehicle drifts due to several reasons from its intended straight path even in the case of no steering input. The multibody dynamic analysis of vehicle drift during accelerating and braking are performed. This paper focuses on modeling and evaluating effects of suspension parameters, differential friction, engine mounting and C.G. location of the vehicle under multibody dynamic simulation environment. Asymmetry of geometry and compliance between left and right side is considered cause of drift. The sensitivities of the suspension parameters are presented for each driving condition. In case of acceleration, the interaction of differential friction and driveshaft stiffness and their influence on drift are also studied. For braking condition, suspension parameters such as initial toe variation of rear coupled torsion beam axle type suspension and kingpin inclination deviation of front suspension are studied including the braking force difference.

Air conditioning is defined as the process of treating air so as to control simultaneously its temperature, humidity, cleanliness and distribution to meet the requirements of the conditioned space. As in the definition, the important actions involved in the operation of an air conditioning system are temperature and humidity control, air purification and movement. For these conditions this paper proposes a Automatic Climate Control(ACC) system of the bus. The system has cooling, heating, and dehumidifying modes, and is governed by dual 8-bit microprocessors. These modes are broken down into sub-modules dealing with control of the compressor, blower speed, damper position, air purifier, ventilators, preheater, air mixing damper and so on.

Current CAE modeling and simulation techniques in the time domain allow, by now, very accurate prediction of many ride-comfort performances of the cars. Nevertheless, the prediction of the steering wheel rotation vibration excited by, for instance, wheel unbalance or asymmetric obstacle impact, often runs into the difficulty of modeling the steering line with sufficient accuracy. For a classic rack and pinion, hydraulic assisted steering line, one of the challenges is to model the complex and non linear properties - stiffness, friction and damping - of the rack-rack case system. This paper proposes a rack model, thought for easy implementation in complex multi-body models, and an identification procedure of its parameters, based on measurements, in the operational range of the wheel unbalance excitation. The measurements have been gathered by specific tests on the components and the test set-up is also shown here.

This paper presents a CAE based approach to accurately simulate and optimize Ride and Handling metrics. Because of the wide range of vehicle phenomena involved, across the variety of frequency ranges, it is essential that the vehicle model includes proper representation of the dynamic properties of the various subsystems (e.g. tires, steering, PT, etc.) Precise correlation between test and simulation for standalone vehicle components and systems is achieved by replicating in the MBS (Multi-body Simulation) the same tests and boundary conditions. This allows the analyst to correctly define those crucial elements and parameters which have the greatest effect on the R&H attribute to be investigated. Setting up the simulation to correctly represent only one single maneuver simulation at a time would not allow the analyst to consider how the dynamic properties of the chassis design variables should be tuned to achieve to best balance and trade-offs.

In contrast to the other types of crash simulations, integrated analysis is needed to perform the side impact simulation, and the acquired injury values are so sensitive that they are difficult to assess by the deformed vehicle structure itself. Accurate FE Euro-side impact dummy (EURO-SID) model is needed to predict the various injury values in Euro side-impact simulation. In the past, rigid body model and coarse FE model have been used. The advantage of these models is low computing power. By the way, they have lack of injury predictability in integrated simulations. The deviations are caused by inaccurate geometry and improper material characteristics expression for individual components. Therefore, new Euro side-impact dummy model is developed through mass (inertia), component and sled validation. In this paper, validation results are illustrated, and their application results in two kinds of full car simulations are introduced.

Low-pressure molding compound (LPMC) is a new kind of composite material which can be used for automotive body panels. LPMC has similar mechanical properties compared to conventional sheet molding compound (SMC) but excellent moldability due to the different thickening system. In this paper, we prepared LPMC hood prototype for a passenger car using a low-cost tooling. Inner panel and outer panel were made of general-density- and low-density-grade LPMC, respectively, in order to maximize weight reduction maintaining surface quality. Physical properties containing tensile strength, flexural modulus, notched Izod impact strength of those samples were investigated. In addition, CAE simulation was also done for strength analysis of the hood assembly.

A multi-body dynamics model that considers elastic deformation of the body was formulated in order to predict transient body deformation, a factor that affects handling. A comparative analysis with body deformation during handling maneuvers identified using a modal forced response method was conducted, and a good correlation was obtained between vehicle dynamic performance, transient body deformation, and the body modal contribution factor.