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Real-time simulation of truck and trailer combinations can be applied to hardware-in-the-loop (HIL) systems for developing and testing electronic control units (ECUs). The large number of configuration variations in vehicle and axle types requires the simulation model to be adjustable in a wide range. This paper presents a modular multibody approach for the vehicle dynamics simulation of single track configurations and truck-and-trailer combinations. The equations of motion are expressed by a new formula which is a combination of Jourdain's principle and the articulated body algorithm. With the proposed algorithm, a robust model is achieved that is numerically stable even at handling limits. Moreover, the presented approach is suitable for modular modeling and has been successfully implemented as a basis for various system definitions. As a result, only one simulation model is needed for a large variety of track and trailer types.

Advanced driver assistance systems (ADAS) are becoming increasingly important for today's commercial vehicles. It is therefore crucial that different ADAS functionalities interact seamlessly with existing electronic control unit (ECU) networks. For example, autonomous emergency braking (AEB) systems directly influence the brake ECU and engine control. It has already become impossible to reliably validate this growing interconnectedness of control interventions in vehicle behavior with prototype vehicles alone. The relevant tests must be brought into the lab at an earlier development stage to evaluate ECU interaction automatically. This paper presents an approach for using hardware-in-the-loop (HIL) simulation to validate ECU networks for extremely diverse ADAS scenarios, while taking into account real sensor data. In a laboratory environment, the sensor systems based on radars, cameras, and maps are stimulated realistically with a combination of simulation and animation.

In the aerospace industry, methods for virtual testing cover an increasing range of test executions carried out during the development and test process of avionics systems. Over the last years, most companies have focused on questions regarding the evaluation and implementation of methods for virtual testing. However, it has become more and more important to seamlessly integrate virtual testing into the overall development process. For instance, a company’s test strategy might stipulate a combination of different methods, such as SIL and HIL simulation, in order to benefit from the advantages of both in the same test process. In this case, efforts concentrate on the optimization of the overall process, from test specification to test execution, as well as the test result evaluation and its alignment with methods for virtual testing.

Real-time simulation of truck and trailer combinations can be applied to hardware-in-the-loop (HIL) systems for developing and testing electronic control units (ECUs). The large number of configuration variations in vehicle and axle types requires the simulation model to be adjustable in a wide range. This paper presents a modular multibody approach for the vehicle dynamics simulation of single track configurations and truck-and-trailer combinations. The equations of motion are expressed by a new formula which is a combination of Jourdain's principle and the articulated body algorithm. With the proposed algorithm, a robust model is achieved that is numerically stable even at handling limits. Moreover, the presented approach is suitable for modular modeling and has been successfully implemented as a basis for various system definitions. As a result, only one simulation model is needed for a large variety of track and trailer types.

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.

Due to tougher legislation on exhaust emissions reduction and the consumer demand for more power and mobility and less fuel consumption, the functionality in today's engine management systems continues to grow. The electronic engine control units (ECUs) have to perform more control tasks using new sensors and actuators, along with the corresponding self-diagnostics (OBD, on-board diagnosis). All this leads to continuously increasing demands on automated hardware-in-the-loop (HIL) test systems. HIL technology has advanced in parallel to the ECUs, and is today an indispensable tool for developing automotive electronics. This paper therefore aims to provide a comprehensive and state-of-the-art survey of HIL test systems for engine controllers. First of all, a brief introduction to the ECU's functionality is given.

In modern vehicles the architecture of electronics is growing more and more complex because both the number of electronic functions – e.g. implemented as software modules – as well as the level of networking between electronic control units (ECUs) is steadily increasing. This complexity leads to greater propagation of failure symptoms, and diagnosing the causes of failure becomes a new challenge. Diagnostics aims at detecting failures such as defect sensors or faulty communication messages. It is subdivided into diagnosis algorithms on an ECU and algorithms running offboard, e.g. on a diagnostic tester. These algorithms have to complement each other in the best possible way. While in the past the diagnosis algorithm was developed late in the development process, nowadays there are efforts to start the development of such algorithms earlier – at least in parallel to developing a new feature itself. This would allow developers to verify the diagnosis algorithms in early design stages.

Model-based development and autocoding have become common practice in the automotive industry over the past few years. The industry is using these methods to tackle a situation in which complexity is constantly growing and development times are constantly decreasing, while the safety requirements for the software stay the same or even increase. The debate is no longer whether these methods are useful, but rather on the conditions for achieving optimum results with them. From the experiences made during the last decade this paper shows some of the key factors helping to achieve success when introducing or extending the deployment of automatic code generation in a model-based design process.

Hardware-in-the-loop (HIL) simulation in the development and test process of vehicle dynamics controllers requires a real-time tractor-trailer simulation model. The hitch coupling must be numerically stable to ensure real-time simulation for various driving maneuvers, particularly at the vehicle's handling limits. This paper presents a robust implementation of tractor-trailer coupling. The equation of motion is formed using a novel formulation which is a combination of Jourdain's Principle and the Articulated Body Algorithm. The paper shows that a robust model for a real-time tractor-trailer simulation can be achieved with the proposed method. Moreover, the approach presented is suitable for modular modeling, is successfully implemented and can also be used as a basis for flexible system definition with an adjustable number of trailer axles.

Increasing diagnosis capabilities in modern engine electronic control units (ECUs), especially in the exhaust path, in terms of emission and engine aftertreatment control utilize on-board NOx prediction models. Nowadays it is an established approach at hardware-in-theloop (HIL) test benches to replicate the engine's steady-state NOx emissions on the basis of stationary engine data. However, this method might be unsuitable for internal ECU plausibility checks and ECU test conditions based on dynamic engine operations. Examples of proven methods for modeling the engine behavior in HIL system applications are so-called mean value engine models (MVEMs) and crank-angle-synchronous (in-cylinder) models. Of these two, only the in-cylinder model replicates the engine’s inner combustion process at each time step and can therefore be used for chemical-based emission simulation, because the formation of the relevant gas species is caused by the inner combustion states.

Hybrid test systems are gaining more and more significance in the aerospace industry. At the heart of these systems is a standardized communication infrastructure. There are many challenges when designing the communication infrastructure. For example, it requires very specific knowledge to boot a hybrid system, manage its configuration process, and start and stop the execution of applications, such as simulations, panels or recorders. Likewise, when testers use a heterogeneous test environment, they cannot commit themselves too much to every single test means and its special characteristics. Nevertheless, testers must always be able to monitor and control every test system. This means, they must be able to determine the current overall system status and the current status of its components and parts. Examples for this are hardware components, such as real-time processors and I/O boards, as well as software applications, such as real-time simulations models on the test system.

Hardware-in-the-loop (HIL) simulation is a real-time testing process that has been proven indispensable for the modern vehicle dynamics, powertrain, chassis and body systems electronic controls development. The high quality standards and robustness of the control algorithms can only be met by means of detailed vehicle plant simulation models. In the last few years, several efforts have been made to develop detailed plant models. Several tools for the vehicle modeling are available in the market and each tool has different and distinct advantages. This paper addresses ways that dSPACE Automotive Simulation Models (ASM) can support the model-based development processes. Additional modern software tools that were used in connection with the ASM are LMS AMESim and Mathworks SimDriveline (of Simscape). ASM is an open Matlab/Simulink model environment used for offline PC based simulation and online real-time platform HIL testing.

The importance of electronics, especially software, has greatly increased over the last few years. Efforts to maintain a high level of software quality have made testing an important part of the development process. With the advent of model-based development, testing methods can be used not only on code level, but also on model level. Next to test execution itself, test development is seen as the most time- and cost-intensive part of the testing process. This paper outlines and classifies current approaches to model-based test development, with the aim of providing guidelines for test developers for choosing the method best suited to the type of system under test and the test objective.

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.

Hardware-in-the-loop (HIL) test benches are indispensable for the development of modern vehicle dynamics controllers (VDCs). They can be regarded as a standard methodology today, because of the extremely safety-critical nature of the multi-sensor and multi-actuator systems used in vehicle dynamics control. The required high quality standards can only be ensured by systematic testing within a virtual HIL environment before going into a real car. This paper aims to provide a condensed technical over-view of state-of-the-art HIL test systems for VDCs, which are currently widely used in passenger cars, in the form of ABS and TCS, as well as ESP, or integrated chassis control, which is just coming onto the market. First, a short introduction to the basic functionality of these types of ECUs is given, and the reasons why HIL testing is necessary and especially useful for VDCs are discussed.

Not only is the number of electronic control units (ECUs) in modern vehicles constantly increasing, the software of the ECUs is also becoming more complex. Both make testing a central task within the development of automotive electronics. Testing ECUs in real vehicles is time-consuming and costly, and comes very late in the automotive development process. It is therefore increasingly being replaced by laboratory tests using hardware-in-the-loop (HIL) simulation. While new software functions are still being developed or optimized, other functions are already undergoing certain tests, mostly on module level but also on system and integration level. To achieve the highest quality, testing must be done as early as possible within the development process. This paper describes the various test phases during the development of automotive electronics (from single function testing to network testing of all the ECUs of a vehicle).

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.

Increasing productivity along the development and verification process of safety-related projects is an important aspect in today’s technological developments, which need to be ever more efficient. The increase of productivity can be achieved by improving the usability of software tools and decreasing the effort of qualifying the software tool for a safety-related project. For safety-critical systems, the output of software tools has to be verified in order to ensure the tools’ suitability for safety-relevant applications. Verification is particularly important for test automation tools that are used to run hardware-in-the-loop (HIL) tests of safety-related software automatically 24/7. This qualification of software tools requires advanced knowledge and effort. This problem can be solved if a tool is suitable for developing safety-related software. This paper explains how this can be achieved for a COTS test automation tool.

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.

This paper presents a demonstrator developed in the European CleanSky2 project MISSION (Modelling and Simulation Tools for Systems Integration on Aircraft). Its scope is the development towards a seamless integrated, interconnected toolchain enabling more efficient processes with less rework time in todays, highly collaborative aerospace domain design applications. The demonstration described here, consists of an open, modular and multitool platform implementation, using specific techniques to achieve fully traceable (early stage) requirements verification by virtual testing. The most promising approach is a model based integration along the whole process from requirements definition to the verified, integrated (and certified) system. Extending previous publications in this series, the paper introduces the motivation and briefly describes the technical background and a potential implementation of a workflow suitable for that target.