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Pumping Mean Effective Pressure (PMEP) is the main factor limiting the improvement of thermal efficiency in a spark-ignition (SI) engine under low load. One of the ways to reduce the pumping loss under low load is to use Cylinder DeActivation (CDA). The CDA aims at reducing the firing density (FD) of the SI engine under low load operation and increasing the mass of air-fuel mixture within one cycle in one cylinder to reduce the throttling effect and further reducing the PMEP. The multi-stroke cycles can also reduce the firing density of the SI engine after some certain reasonable design, which is feasible to improve the thermal efficiency of the engine under low load in theory. The research was carried out on a calibrated four-cylinder SI engine simulation platform. The thermal efficiency improvements of the 6-stroke cycle and 8-stroke cycle to the engine performance were studied compared with the traditional 4-stroke cycle under low load conditions.

In order to correctly predict the impact of tire dimensions and properties on ride comfort in the early phases of the vehicle development process, it is necessary to fully understand their influence on the dynamic tire behavior. The currently existing models for reproducing tire forces often need many measurements for parametrization, simplify physical properties by empiric functions, or have an insufficient simulation speed to analyze many variants in the short periods of early process phases. In the following analysis, a tire concept model is presented, which utilizes relations between the static and dynamic behavior of tires in order to efficiently predict the dynamic forces in the vertical and longitudinal direction during obstacle crossing. The model allows for efficient parametrization by minimizing the number of parameters as well as measurements and ensures a high simulation speed. To realize this, initially, a selection of tires is measured on a tire test rig.

Software complexity of vehicles is constantly growing especially with additional autonomous driving features being introduced. This increases the risk for bugs in the system, when the car is delivered. According to a car manufacturer, more than 90% of availability problems corresponding to Electronic Control Unit (ECU) functionality are either caused by software bugs or they can be resolved by applying software updates to overcome hardware issues. The main concern are sporadic errors which are not caught during the development phase since their trigger condition is too unlikely to occur or is not covered by the tests. For such systems, there is a need of safe and secure infield diagnosis. In this paper we present a tool software architecture with remote access, which facilitates standard read/write access, an efficient channel interface for communication and file I/O, and continuous trace.

It’s well known that startup process of proton exchange membrane fuel cells (PEMFCs) under subzero temperature is extremely significant because of its influence on fuel cell performance and durability. In the study, a quasi-2D numerical model is developed and dynamic equations of mass conservation, energy conservation, membrane water conservation, ice conservation, species conservation are all considered. Three different hydrogen supply modes are studied in detail: flow-through anode (FTA) mode, dead-ended anode (DEA) mode and off-gas recirculation (OR) mode. It is found that the local current density (LCD) and temperature distribution vary remarkably along flow channel in OR mode as t > 500s due to nitrogen crossover and accumulation. During the cold start operation, the DEA mode and OR mode hold more water in anode catalyst layer (ACL) which reduces the effects of hydraulic permeation, resulting in more ice formation in cathode catalyst layer (CCL) and slower temperature rising.

A new two-dimensional wall-flow DPF microstructure model has been developed in this paper to investigate the particle deposition distribution in DPF channels and the deep-bed filtration process of DPF. The substrate wall of the DPF having a thickness of L is divided into several layers with a uniform thickness of Δy along the cross-wall direction, and each layer has specific porosity and pore size. The pressure drop, particle deposition distribution and the dynamic deep-bed filtration process of the DPF with inhomogeneous wall structure are studied under various space velocities. Besides, the differences on DPF’s performance brought by the inhomogeneous wall structure are discussed by comparing with a homogeneous wall structure.

The increasingly stringent requirements in relation to emission reduction and onboard diagnostics are pushing the Chinese automotive industry toward more innovative solutions and a rapid increase in electronic control performance. To manage the system complexity the architecture will require being well structure on hardware and software level. The paper introduces GEMS-K1 (Gasoline Engine Management System - Kit 1). GEMS-K1 is a platform being compliant with Euro IV emission regulation for gasoline engines. The application software is developed using modeling language, the code is automatically generated from the model. The driver software has a well defined structure including microcontroller abstraction layer and ECU abstraction layer. The hardware is following design rules to be robust, 100% testable and easy to manufacture. The electronic components use the latest innovation in terms of architecture and technologies.

P2 hybrid electric vehicle is the single-motor parallel configuration integrating with an engine disconnect clutch (EDC) between the engine and the motor. The key point with P2 hybrid electric vehicle is to start the engine utilizing the single driving motor while still propelling the vehicle, which requires an appropriate engine-start control strategy and a high mechanical performance of EDC. Since the space for EDC is limited, EDC torque response is difficult to follow the torque command, which complicates the issue of precisely controlling the clutch. Consequently, methods proposed in massive papers are inappropriate for current EDC of target vehicle. Considering that slip control of shifting clutch also contributes to reducing impact of engine start assisted by EDC, a detailed engine-start control strategy was proposed to simplify the control of EDC for being applied to actual target vehicle.

The aerodynamic optimization of an AUDI Q5 vehicle is presented using the continuous adjoint approach within the OpenFOAM framework. All calculations are performed on an unstructured automatically generated mesh. The primal flow, which serves as input for the adjoint method, is calculated using the standard CFD process at AUDI. It is based on DES calculations using a Spalart-Allmaras turbulence model. The transient results of the primal solution are time averaged and fed to a stationary adjoint solver using a frozen turbulence assumption. From the adjoint model, drag sensitivity maps are computed and measures for drag reduction are derived. The predicted measures are compared to CFD simulations and to wind tunnel experiments at 1:4 model scale. In this context, general challenges, such as convergence and accuracy of the adjoint method are discussed and best practice guidelines are demonstrated.

The trend towards even more sophisticated driver assistance systems and growing automation of driving sets new requirements for the robustness and availability of the involved automotive systems. In case of an error, today it is still sufficient that safety related systems just fail safe or silent to prevent safety related influence of the driving stability resulting in a functional deactivation. But the reliance on passive mechanical fallbacks in which the human driver taking over control, being inevitable in such a scenario, is expected to get more and more insufficient along with a rising degree of driving automation as the driver will be given longer reaction time. The advantage of highly or even fully automated driving is that the driver can focus on other tasks than controlling the car and monitoring it’s behavior and environment.

A wide-ranging investigation into the sensitivity of the hybrid RANS-LES based OpenFOAM CFD process at Audi was undertaken. For a range of cars (A1, TT, Q3 & A4) the influence of the computational grid resolution, turbulence model formulation and spatial & temporal discretization is assessed. It is shown that SnappyHexMesh, the Cartesian-prismatic built-in OpenFOAM mesher is unable to generate low y+ grids of sufficient quality for the production Audi car geometries. For high y+ grids there was not a consistent trend of additional refinement leading to improved correlation between CFD and experimental data. Similar conclusions were found for the turbulence models and numerical schemes, where consistent improvements over the baseline setup for all aerodynamic force coefficients were in general not possible. The A1 vehicle exhibited the greatest sensitivity to methodology changes, with the TT showing the least sensitivity.

Computational Fluid Dynamics (CFD) is state of the art in the aerodynamic development process of vehicles nowadays. With increasing computer power the numerical simulations including meshing and turbulence modeling are capturing the complex geometry of vehicles and the flow field behavior around and behind a bluff body in more detail. The ultimate goal for realistic automotive simulations is to model the under-hood as well. In this study vehicle simulations using the finite volume open source CFD program OpenFOAM® are validated with own experiments on a modified generic quarter-scale SAE body with under-hood flow. A model radiator was included to take account of the pressure drop in the under-hood compartment. Force and pressure measurements around the car, total-pressure and hot-wire measurements in the car flow field and surface flow patterns were simulated and compared with the experiment.

As the demand for enhanced comfort, safety and differentiation with new features continues to grow and as electronics and software enable most of these, the number of electronic units or components within automobiles will continue to increase. This will increase the overall system complexity, specifically with respect to the number of controller actuators such as e-motors. However, hard constraints on cost and on physical boundaries such as maximum power dissipation per unit and pin-count per unit/connector require new solutions to alternative system partitioning. Vehicle manufacturers, as well as system and semiconductor suppliers are striving for increased scalability and modularity to allow for most cost optimal high volume configurations while featuring platform reuse and feature differentiation. This paper presents new semiconductor based approaches with respect to technologies, technology mapping and assembly technologies.

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.

Today the majority of power electronics is developed based on the requirements set by the main fields of application e.g. power generation, power supply, industrial drive and traction. With introduction to automotive applications new requirements have to be taken into account. This paper discusses how interconnection technologies for power semiconductors can be improved to meet the demand for higher temperature capability in HEV applications.

Hybrid vehicle simulation methods combine physical test articles (vehicles, suspensions, etc.) with complementary virtual vehicle components and virtual road and driver inputs to simulate the actual vehicle operating environment. Using appropriate components, hybrid simulation offers the possibility to develop more accurate physical tests earlier, and at lower cost, than possible with conventional test methods. MTS Systems has developed Hybrid System Response Convergence (HSRC), a hybrid simulation method that can utilize existing durability test systems and detailed non-real-time virtual component models to create an accurate full-vehicle simulation test without requiring road load data acquisition. MTS Systems and Audi AG have recently completed a joint evaluation project for the HSRC hybrid simulation method using an MTS 329 road simulator at the Audi facility in Ingolstadt, Germany.

The recent improvements in automotive electronics have had a tremendous impact on safety, comfort and emissions. But the continuous increase of the volume of electronic equipment in cars (representing more than 25% of purchasing volume) as well as the increasing system complexity represent a new challenge to quality, post-sales customer support and maintenance. Identifying a fault in a complex network of ECUs, where the different functions are getting more and more intricate, is not an easy task. It can be shown that with the levels of reliability common in 1980, an upper-range automobile of today could never function fault-free. On-Board-Diagnostics (OBD) concepts are emerging to assist the maintenance personnel in localizing the source of a problem with high accuracy, reducing the vehicle repair time, repair costs and costs of warranty claims.

In decade years, Spark Ignition-Controlled Auto Ignition (SI-CAI) hybrid combustion, also called Spark Assisted Compression Ignition (SACI) has shown its high-efficiency and low emissions advantages. However, high dilution causes the problem of unstable initial ignition and flame propagation, which leads to high cyclic variation of heat release and IMEP. The instability of SI-CAI hybrid combustion limits its dilution degree and its ability to improve the thermal efficiency. In order to solve instability problems and expand the dilution boundary of hybrid combustion, micro flame ignition (MFI) strategy is applied in gasoline hybrid combustion engines. Small amount of Dimethyl Ether (DME) chosen as the ignition fuel is injected into cylinder to form micro flame kernel, which can stabilize the ignition combustion process.

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).

The SCR after treatment system is already in production for passenger car engines with a single exhaust system. In this case, the exhaust system has to be designed very carefully to optimize the Ammonia distribution on the catalyst and therefore the DeNOx potential. The application to V8 engines with two turbochargers delivering the gas into two separated DOC & DPF units is an additional challenge. This paper describes the different optimization steps of such an exhaust system and the tools used during this work. After a design phase to integrate the SCR system in the exhaust geometry, a first CFD study was conducted to evaluate the performance of the basic system using one or two urea injectors. An optimization of the connection of the two tubes, directly in front of the SCR catalyst, has been designed using further CFD calculations as well as a marker gas SF6 on a cold flow bench.

During the aero-engine operation, the compressor blades are subjected to periodic inertial force and aerodynamic excitation caused by blade rotation and airflow disturbance, respectively. Under the coupling alternating loads, the blade is prone to high cycle fatigue failure. In this paper, a time domain calculation model of fluid-structure interaction (FSI) is established to study the vibration characteristics of the blade and its failure modes are analyzed. Then, the fatigue damage of the blade under multi-level loading is evaluated by the nonlinear damage accumulation model. Considering the coupling effect of the airflow and the blade, computational fluid dynamics (CFD) is applied to calculate the aerodynamic parameters on the blade surface under different working conditions, which is imported to the finite element (FE) model to analyze the dynamic characteristics.