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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.

The newly released Distributed System Interface 3 (DSI3) Bus Standard specification defines three modulation levels form which 16 valid symbols are coded. This complex structure is best decoded with symbol pattern recognition. This paper proposes a simplification of the correlation score calculation that sharply reduces the required number of operations. Additionally, the paper describes how the pattern recognition is achieved using correlation scores and a decoding algorithm. The performance of this method is demonstrated by mean of simulations with different load models between the master and the sensors and varying noise injection on the channel. We prove than the pattern recognition can decode symbols without any error for up to 24dBm.

This paper discusses the RDC method utilizing delta-sigma analog-to-digital converter hardware module (DSADC) integrated in the Infineon's microcontroller family. With its higher resolution capability when compared to the regularly used ADC with successive-approximation (SAR), DSADC seems to have more potential. On the other hand, DSADC's inherent properties, such as asynchronous sampling rate and group delay, which when not handled properly, would have negative effects to the rotor positioning system. The solution to overcome those side-effects involves utilization of other internal microcontroller's resources such as timers and capture units, as well as additional software processing run inside CPU. The rotor positioning system is first modeled and simulated in high-level simulation language environment (Matlab and Simulink) in order to predict the transient- and steady state behaviors. The group delay itself is obtained by simulating the model of DSADC module implementation.

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.

Modeling techniques matter a lot in many fields of engine engineering. Models are requested not only for control design but also for dynamic prediction. However, problems might be encountered during modeling process either because of the system complexity or the unaffordable modeling cost. As a result, a new modeling technique based on disturbance estimation is proposed in this paper. By employing the proposed modeling technique, models are set up in real time with the online information from input and output. The uncertainties of system dynamics are handled as internal disturbance of the system, while the perturbation from outside are taken as the external disturbance, and the combination of the two can be estimated online by a kind of active observer called extended state observer (ESO).

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.

Although supercharged system has been widely employed in downsized engines, the effect of supercharging on the intake flow characteristics remains inadequately understood. Therefore, it is worthwhile to investigate intake flow characteristics under high intake pressure. In this study, the supercharged intake flow is studied by experiment using steady flow test bench with supercharged system and transient flow simulation. For the steady flow condition, gas compressibility effect is found to significantly affect the flow coefficient (Cf), as Cf decreases with increasing intake pressure drop, if the compressibility effect is neglected in calculation by the typical evaluation method; while Cf has no significant change if the compressibility effect is included. Compared with the two methods, the deviation of the theoretical intake velocity and the density of the intake flow is the reason for Cf calculation error.

Nowadays, proton exchange membrane (PEM) fuel cell is widely seen as a promising energy conversion device especially for transportation application scenario because of its high efficiency, low operation temperature and nearly-zero road emission. Extensive modeling work have been done based on different dimensions during the past decades, including one-dimensional (1D), two-dimensional (2D), three-dimensional (3D) and intermediate combinations in between (e.g. “1+1D”). 1D model benefits from a rationally-chosen set of assumptions to obtain excellent calculation efficiency, yet at the cost of accuracy to some extent. In contrast, 3D model has great advantage over 1D model on acquiring more comprehensive information inside the fuel cell. For macro-scale modeling work, one compromise aiming to realize both acceptable computation speed and reasonable reflection of cell operation state is to simplify the membrane electrode assembly (MEA).

Lean NOx trap (LNT) is a great potential NOx abatement method for lean-burn gasoline engines in consideration of exhaust aftertreatment cost and installation space. NOx firstly is adsorbed on storage sites during the lean-burn period, then reduced to N2 under catalysis of the catalyst sites in the rich-burn phase. There must be a spillover of NOx species between both types of sites. For a better understanding of this spillover process of NOx species between Pt (as the catalytic center) and BaO sites (as storage components in commercial catalyst), this work focused on the vital first step of spillover, the adsorption of NOx on clean substrate surface (γ-Al2O3 (110) surface) and Ba\Pt cluster supported by the surface. Based on first principles software VASP (Vienna Ab-initio Simulation Package), the most stable adsorption structures of NO with Pt3 clusters and (BaO)3 clusters on carrier γ- Al2O3 (110) surface were confirmed and the adsorption energy of these structures were compared.

Noise source identification and separation of internal combustion engines is an effective tool for engine NVH (noise, vibration and harshness) development. Among various experimental approaches, noise source identification using signal processing has attracted extensive attention because of that the signal can be easily acquired and the requirements for equipment is relatively low. In this paper, variational mode decomposition (VMD) combined with independent component analysis (ICA) is used for noise source identification of a turbo-charged gasoline engine. Existing algorithms have been proved to be effective to extract signal features but also have disadvantages. One of the key problems in presently used method is that the main components of the signal, i.e. the main source of the noise, are unknown in advance. Thus the parameters selection of signal processing algorithms, which has a significance influence on the identification result, has no uniform criterion.

This work numerically investigates the detailed combustion kinetics of partially premixed combustion (PPC) in a diesel engine under three different premixed ratio fuel conditions. A reduced Primary Reference Fuel (PRF) chemical kinetics mechanism was coupled with CONVERGE-SAGE CFD model to predict PPC combustion under various operating conditions. The experimental results showed that the increase of premixed ratio (PR) fuel resulted in advanced combustion phasing. To provide insight into the effects of PR on ignition delay time and key reaction pathways, a post-process tool was used. The ignition delay time is related to the formation of hydroxyl (OH). Thus, the validated Converge CFD code with the PRF chemistry and the post-process tool was applied to investigate how PR change the formation of OH during the low-to high-temperature reaction transition. The reaction pathway analyses of the formations of OH before ignition time were investigated.

Strategies to suppress knock have been extensively investigated to pursue thermal efficiency limits in downsized engines with a direct-injection spark ignition. Comprehensive considerations were given in this work, including the effects of second injection timing and injector location on knock combustion in a downsized gasoline engine by large eddy simulation. The turbulent flame propagation is determined by an improved G-equation turbulent combustion model, and the detailed chemistry mechanism of a primary reference fuel is employed to observe the detailed reaction process in the end-gas auto-ignition process. The conclusions were obtained by comparing the data to the baseline single-injection case with moderate knock intensity. Results reveal that for both arrangements of injectors, turbulence intensity is improved as the injecting timing is retarded, increasing the flame propagation speed.

Aiming at the problem of poor robustness after the combination of lateral kinematics control and lateral dynamics control when an autonomous vehicle decelerates and changes lanes to overtake at a certain distance. This paper proposes a trajectory determination and tracking control method based on a PI-MPC dual algorithm controller. To describe the longitudinal deceleration that satisfies the lateral acceleration limit during a certain distance of lane change, firstly, a fifth-order polynomial and a uniform deceleration motion formula are established to express the lateral and longitudinal displacements, and a model prediction controller (MPC) is used to output the front wheel rotation angle. Through the dynamic formula and the speed proportional-integral (PI) controller to control and adjust the brake pressure.

As a major power source, diesel engines are being widely used in a variety of fields. However, because of complex structure, some faults which cannot be detected by direct signals would occur on engines and even lead to accidents. Among all kinds of indirect signals, vibration signal is the most common choice for faults detection without disassemble because of its convenience and stability. This paper proposed a novel approach for detecting multiple engine faults based on block vibration signals using variational mode decomposition (VMD) and echo state network (ESN). Since the quadratic penalty has a great influence on adaptable VMD that may make expected component signals cannot be extracted exactly, this paper proposed a dynamic quadratic penalty value, which will change with decomposing level. This paper selected a best dynamic quadratic penalty value by analyzing a large amount of data and results showed that this approach can decompose signals more exactly.

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.

Flash boiling spray is effective in improving the atomization and evaporation characteristics for gasoline direct injection engines. However, for a multi-hole injector the morphology structure of spray has an obvious change with the fuel temperature increasing or the ambient pressure decreasing, which influences the process of mixture formation and flame propagation. Specially, the spray collapses with both long penetration and a narrow spray angle above certain high superheat degree, which deteriorates air/fuel mixing and hence increases emissions. It is not desired for engine applications while the mechanism of spray structure transformation for multi-hole injector still remains unclear. In the present study, a systematic flash boiling spray model for multi-hole injector is built to investigate the flash boiling spray of multi-hole injector.

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.

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.