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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.

This paper proposes a new integrated chassis control (ICC) using a predictive model-based control (MPC) for optimal allocation of sub-chassis control systems where a predictive model has 6 Degree of Freedom (DoF) for rigid body dynamics. The 6 DoF predictive vehicle model consists of longitudinal, lateral, vertical, roll, pitch, and yaw motions while previous MPC research uses a 3 DoF maximally predictive model such as longitudinal, lateral and yaw motions. The sub-chassis control systems in this paper include four wheel individual braking torque control, four wheel individual driving torque control and four corner active suspension control. Intermediate control inputs for sub-chassis control systems are simplified as wheel slip ratio changes for driving and braking controls and vertical suspension force changes for an active suspension control.

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.

This paper presents an adaptation method of equivalent factor in equivalent consumption minimization strategy (ECMS) of fuel cell hybrid electric vehicle (FCHEV) using hilly road information. Instantaneous optimization approach such as ECMS is one of real-time controllers. Furthermore, it is widely accepted that ECMS achieves near-optimum results with the selection of the appropriate equivalent factor. However, a lack of hilly road information no longer guarantees near-optimum results as well as charge-sustaining of ECMS under hilly road conditions. In this paper, first, an optimal control problem is formulated to derive ECMS analytical solution based on simplified models. Then, we proposed updating method of equivalent factor based on sensitivity analysis. The proposed method tries to mimic the globally optimal equivalent factor trajectory extracted from dynamic programming solutions.

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.

The reduction of vehicle exhaust particle emissions is a success story of European legislation. Various particle number (PN) counters and calibration procedures serve as tools to enforce PN emission limits during vehicle type approval (VTA) or periodical technical inspection (PTI) of in-use vehicles. Although all devices and procedures apply to the same PN-metric, they were developed for different purposes, by different stakeholder groups and for different target costs and technical scopes. Furthermore, their calibration procedures were independently defined by different stakeholder communities. This frequently leads to comparability and interpretation issues. Systematic differences of stationary and mobile PN counters (PN-PEMS) are well-documented. New, low-cost PTI PN counters will aggravate this problem. Today, tools to directly compare different instruments are scarce.

Wheel slip control system have found a remarkable penetration in all car segments. The information on the wheel behavior has lead to further developments which control the brake performance as well as the driving of the car in general. Latest systems introduced especially on luxury cars use wheel individual brake intervention to ensure vehicle stability under various driving maneuvers within the physical limits. Such systems use vehicle dynamic sensors and special hydraulics which serve as energy source for the automatic brake application. The technical effort of such systems like the Dynamic Stability Control DSC has limited the installation to upper class cars so far. New approaches are required to allow for a more wide spread penetration. Optimized hydraulics together with a rational design of the electronics seems to offer a basis for a more cost effective design.

The series-parallel hybrid electric vehicle(HEV), which employs a planetary gear set to combine one internal combustion engine(ICE) and two electric motors(EMs), can take advantages of both series and parallel hybrid system. The efficient powertrain operating point of the system can be obtained by the instantaneous optimization of equivalent fuel consumption. However, heavy computational requirements and variable constraints of the optimization process make it difficult to build real-time control strategy. To overcome the difficulty, this study suggests the control strategy which divides the optimization process into 2 stages. In the first stage, a target of charge/discharge power is determined based on equivalent fuel consumption, then in the second stage, an engine operating point is determined taking power transfer efficiency into account.

In this paper, a design procedure for the optimized light weight front cross member, which is a sub frame of the car chassis, without sacrificing basic functional requirements is presented. As the first step, optimal structural integrity was calculated and extracted using a CAE technique with the available volume constraint of the package layout. Quantitative design loads for the cross member was achieved by measurement. Dynamic load analysis using ADAMS was also performed to determine the loads. Later, these calculated loads were applied to the FEM stress analysis of the cross member. Furthermore, durability analysis was also performed using load profile database measured from ‘Hyundai Motor Co. Proving Ground’. Four constant amplitude durability tests and two static tests were performed on the cross member prototypes to confirm design reliability.

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.

An increasing number of cars which are being used to foster leisure and a convenient life for consumers are being outfitted with roof racks and/or cross bars. This trend of installing roof racks is partly for the function of carrying objects on the roof of the vehicle and partly as a way to affect the style and exterior look of the vehicle. Therefore, the application of roof racks and cross bars is becoming increasingly important in the automotive industry. Because of the expanding application of roof racks on vehicles, the challenge of reducing wind noise caused by exposed cross bars becomes the main issue in this field. For solving this problem, the cross bar shape is designed and evaluated in the development stage, and if there is a problem, it is re-designed and re-evaluated many times. This repetitive corrective action is called “trial and error”.

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.

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.