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Due to the rapidly increasing number of electronic control units (ECUs) in modern vehicles, software and ECU testing plays a major role within the development of automotive electronics. To ensure effective as well as efficient testing within the whole development process, a seamless transition in terms of the reusability of tests and test data as well as powerful and efficient means for developing and describing tests are required. This paper therefore presents a new integration approach for modern test development and test management. Besides a very easy-to-use way of describing tests graphically, the main focus of the new approach is on the management of a large number of tests, test data, and test results, allowing close integration into the automotive development processes.

Compared to conventional injection techniques, Gasoline Direct Injection (GDI) has a lot of advantages such as increased fuel efficiency, high power output and low emission levels, which can be more accurately controlled. Therefore, this technique is an important topic of today's injection system research. Although the operating conditions of GDI injectors are simpler from a numerical point of view because of smaller Reynolds and Weber numbers compared to Diesel injection systems, accurate simulations of the breakup in the vicinity of the nozzle are very challenging. Combined with the complications of experimental techniques that could be applied inside the nozzle and at the nozzle exit, this is the reason for the lack of understanding the primary breakup behavior of current GDI injectors.

A new approach is presented to modelling wall heat transfer in the exhaust port and manifold within 1D gas exchange simulation to ensure a precise calculation of thermal exhaust enthalpy. One of the principal characteristics of this approach is the partition of the exhaust process in a blow-down and a push-out phase. In addition to the split in two phases, the exhaust system is divided into several sections to consider changes in heat transfer characteristics downstream the exhaust valves. Principally, the convective heat transfer is described by the characteristic numbers of Nusselt, Reynolds and Prandtl. However, the phase individual correlation coefficients are derived from 3D CFD investigations of the flow in the exhaust system combined with Low-Re turbulence modelling. Furthermore, heat losses on the valve and the seat ring surfaces are considered by an empirical model approach.

Hypoid gears transmission error (TE) is a metric that is usually used to evaluate their NVH performance in component level. The test is usually done at nominal position as well as out of positions where the pinion and gear are moved along their own axis and also along offset direction to evaluate sensitivity of the measured TE to positional errors. Such practice is crucial in practical applications where the gear sets are inevitably exposed to off position conditions due to a) housing machining and building errors, b) deflections of housing, bearings, etc. under load and c) thermal expansions or contractions of housing due to ambient temperature variations. From initial design to development stage, efforts should be made to design the gear sets to be robust enough to all combinations of misalignments emanated from all three mentioned categories.

Automotive technology is rapidly changing with electrification of vehicles, driver assistance systems, advanced safety systems etc. This advancement in technology is making the task of validation and verification of embedded software complex and challenging. In addition to the component testing, integration testing imposes even tougher requirements for software testing. To meet these challenges dSPACE is continuously evolving the Hardware-In-the-Loop (HIL) technology to provide a systematic way to manage this task. The paper presents developments in the HIL hardware technology with latest quad-core processors, FPGA based I/O technology and communication bus systems such as Flexray. Also presented are developments of the software components such as advanced user interfaces, GPS information integration, real-time testing and simulation models. This paper provides a real-world example of implication of integration testing on HIL environment for Chassis Controls.

The technological development in the field of automotive electronics is proceeding at almost break-neck speed. The functions being developed and integrated into cars are growing in complexity and volume. With the increasing number and variety of sensors and actuators, electronics have to handle a greater amount of data, and the acquisition and generation of I/O signals is also growing in complexity, for example, in engine management applications. Moreover, intelligent and complex algorithms need to be processed in a minimum of time. This all intensifies the need for Rapid Control Prototyping (RCP), a proven method of decisively speeding up the model-based software development process of automotive electronic control units (ECUs) [1],[2]. All these demanding tasks, including connecting sensors and actuators to the RCP system, need to be performed within a standard prototyping environment.

The development of perception functions for tomorrow’s automated vehicles is driven by enormous amounts of data: often exceeding a gigabyte per second and reaching into the terabytes per hour. Data is typically gathered by a fleet of dozens of mule vehicles which multiply the data generated into the hundreds of petabytes per year. Traditional methods for fueling data-driven development would record every bit of every second of a data logging drive on solid-state drives located on a PC in the vehicle. Recorded data must then be exported from these drives using an upload station which pushes to the data lake after arriving back at the garage. This paper considers different techniques for curating logged data.

One of the basic topics in the design of new injection systems for DI Diesel engines is to decrease the soot emissions. A promising approach to minimize soot production are nozzles with clustered holes. A basic idea of the Cluster Configuration (CC) nozzles is to prevent a fuel rich area in the center of the flame where most of the soot is produced, and to minimize the overall soot formation in this way. For this purpose each hole of a standard nozzle is replaced by two smaller holes. The diameter of the smaller holes is chosen so that the flow rate of all nozzles should be equal. The basic strategy of the cluster nozzles is to provide a better primary break up and therefore a better mixture formation caused by the smaller nozzle holes, but a comparable penetration length of the vapor phase due to merging of the sprays. Three possible arrangements of the clustered holes are investigated in this study. Both the cluster angle and the orientation to the injector axis are varied.

Due to increasing environmental awareness, standards for pollutant and CO2 emissions are getting stricter in most markets around the world. In important markets such as Europe, also the emissions during real road driving, so called “Real Driving Emissions” (RDE), are now part of the type approval process for passenger cars. In addition to the proceeding hybridization and electrification of vehicles, the complexity and degrees of freedom of conventional powertrains with internal combustion engines (ICE) are also continuing to increase in order to comply with stricter exhaust emission standards. Besides the different requirements placed on vehicle emissions, the drivability capabilities of passenger vehicles desired by customers, are essentially important and vary between markets.

Model-based software development and automatic code generation have become increasingly established in recent years. The automotive industry has widely adopted and successfully deployed these methods in many different series production programs worldwide. This brought various benefits, such as a reduction in development times, improved quality due to more precise specifications, and early verification and validation by means of simulation. At the same time, more and more safety-related and safety-critical systems have been - and will be -introduced into modern vehicles. Common examples are active front steering, adaptive cruise-control, and integrated chassis control. This leads to the question, if and how model-based design and automatic production code generation can be applied to the development of safety-critical systems.

Modern vehicles become increasingly software intensive. Software development therefore is critical to the success of the manufacturer to develop state of the art technology. Standards like ISO 26262 recommend requirement-based verification and test cases that are derived from requirements analysis. Agile development uses continuous integration tests which rely on test automation and evaluation. All these drove the development of a new model-based software verification environment. Various aspects had to be taken into account: the test case specification needs to be easily comprehensible and flexible in order to allow testing of different functional variants. The test environment should support different use cases like open-loop or closed-loop testing and has to provide corresponding evaluation methods for continuously changing as well as for discrete signals.

Especially for internal combustion engine simulations, various combustion models rely on the laminar burning velocity. With respect to computational time needed for CFD, the calculation of laminar burning velocities using a detailed chemical mechanism can be replaced by incorporation of approximation formulas, based on rate-ratio asymptotics. This study revisits an existing analytical approximation formula [1]. It investigates applicable temperature, pressure, and equivalence ratio ranges with special focus on engine combustion conditions. The fuel chosen here is methane and mixtures are composed of methane and air. The model performance to calculate the laminar burning velocity are compared with calculated laminar burning velocities using existing state of the art detailed chemical mechanisms, the GRI Mech 3.0 [2], the ITV RWTH [3], and the Aramco mechanism [4].

This paper describes a new production code generator that meets both the requirements of code developers for efficient and reliable production code, as well as the desire of system engineers to establish a control design process based on simulation models that double as executable specifications for the ECU software. The production code generator supports automatic scaling, generates optimized fixed-point C code for microcontrollers like the Motorola 683xx, Siemens C16x, and Hitachi SH-2, and produces ASAP2 [1] calibration information. Benchmark results show that the autogenerated code can match or even exceed the efficiency of typical handwritten production code. Code quality is assured by design and by systematic, automatic, and extremely comprehensive test procedures.

Today, automated vehicles mostly rely on ego vehicle sensors such as cameras, radar or LiDAR sensors that are limited in their sensing capability and range. Vehicle-to-everything (V2X) communication has the potential to appropriately complement these sensors and even allow for a cooperative, proactive interaction of vehicles. As such, V2X communication might play a vital role on the way to smart and efficient traffic solutions. In the public funded research project UK Autodrive, we are currently investigating and experimentally evaluating V2X-based applications based on dedicated short range communication (DSRC). Moreover, the novel application intersection priority management (IPM) is part of the research project. IPM aims at automating intersections in such a way that vehicles can pass safely and even more efficiently without the use of traffic lights or signs.

This paper will first introduce and classify the basic principles of architecture-driven software development and will briefly sketch the presumed development process. This background information is then used to explain extensions which enable current behavior modeling and code generation tools to operate as software component generators. The generation of AUTOSAR software components using dSPACE's production code generator TargetLink is described as an example.

This paper introduces different modeling approaches of crankshafts, compares the refinement levels and discusses the difference between the results of the crankshaft durability calculation methodologies. A V6 crankshaft is considered for the comparison of the refinement levels depending on the deviation between the signals such as main bearing forces and deflection angle. Although a good correlation is observed between the results in low speed range, the deviation is evident through the mid to high speed ranges. The deviation amplitude differs depending on the signal being observed and model being used. An inline 4 crankshaft is considered for the comparison of the durability results. The analysis results show that the durability potential is underestimated with a classical crankshaft calculation approach which leads to a limitation of maximum speed of 5500 rpm.

Direct injection (DI) compressed natural gas (CNG) engines are emerging as a promising technology for highly efficient and low-emission engines. However, the design of DI systems for compressible gas is challenging due to supersonic flows and the occurrence of shocks. An outwardly opening poppet-type valve design is widely used for DI-CNG. The formation of a hollow cone gas jet resulting from this configuration, its subsequent collapse, and mixing is challenging to characterize using experimental methods. Therefore, numerical simulations can be helpful to understand the process and later to develop models for engine simulations. In this article, the results of high-fidelity large-eddy simulation (LES) of a stand-alone injector are discussed to understand the evolution of the hollow cone gas jet better.

Within a public founded project test cell investigations were undertaken to identify parameters which predominantly influence the development of critical deposits in injection nozzles. A medium-duty diesel engine was operated in two different coking cycles with a zinc-free lubricant. One of the cycles is dominated by rated power, while the second includes a wide area of the operation range. During the experiments the temperatures at the nozzle tip, the geometries of the nozzle orifice and fuel properties were varied. For a detailed analysis of the deposits methods of electron microscopy were deployed. In the course of the project optical access to all areas in the nozzle was achieved. The experiments were evaluated by means of the monitoring of power output and fuel flow at rated power. The usage of a SEM (scanning electron microscope) and a TEM (transmission electron microscope) revealed images of the deposits with a magnification of up to 160 000.

Function models have a well-established position in automotive software development. Formal system models, on the other hand, are rare. This article describes the various aspects of function and system models, focusing mainly on AUTOSAR-compatible models. It also depicts the challenges for future overall models that combine the function models and the system model, and the resulting benefits, such as early system verification via PC-based simulations.

The application of a communication infrastructure for hybrid test systems is currently a topic in the aerospace industry, as also in other industries. One main reason is flexibility. Future laboratory tests means (LTMs) need to be easier to exchange and reuse than they are today. They may originate from different suppliers and parts of them may need to fulfill special requirements and thus be based on dedicated technologies. The desired exchangeability needs to be achieved although suppliers employ different technologies with regard to specific needs. To achieve interoperability, a standardized transport mechanism between test systems is required. Designing such a mechanism poses a challenge as there are several different types of data that have to be exchanged. Simulation data is a prominent example. It has to be handled differently than control data, for example. No one technique or technology fits perfectly for all types of data.