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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.

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.

Electric drives are growing in importance in automotive applications, especially in hybrid electric vehicles (HEV) and in the vehicle dynamics area (steering systems, etc.). The challenges of real-time hardware-in-the-loop (HIL) simulation and testing of electric drives are addressed in this paper. In general, three different interface levels between the electric drive and the hardware-inthe-loop system can be distinguished: the signal level (1), the electrical level (2) and the mechanical level (3). These interface levels, as well as modeling and I/O-related aspects of electric drives and power electronics devices, are discussed in detail in the paper. Finally, different solutions based on dSPACE simulator technology are presented, for both hybrid vehicle and steering applications.

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.

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.

This presentation focuses on several examples of partnerships between tool suppliers and embedded software developers in which state-of-the-art tools are used to optimize a variety of electric and hybrid vehicle architectures. Projects with Automotive OEMs, Tier One Suppliers as well as with academic institutions will be described. Due to the growing complexity in multiple electronic control units (“ECUs”) inter-communicating over numerous network bus systems, combined with the challenge of controlling and maintaining charges for electric motors, vehicle development would be impossible without use of increasingly sophisticated tools. Hybrid drive trains are much more complex than conventional ones, they have at least one degree of freedom more.

Due to the continuously increasing number of electronic control units (ECUs) in modern cars, and their growing complexity, automated tests not only of single ECUs but also of interconnected ECUs have become an important step in the development of automotive electronics. These tasks require new test systems. This paper describes the problems engineers face when developing and testing today's car electronics, as well as a high-end hardware-in-the-loop (HIL) tool set (hardware, software, models) applied to the testing of four networked ECUs for engine management, vehicle dynamics control, automatic transmission, and an active suspension system. The tool set comprises general features needed for HIL tests, like automated code generation for real-time models using MATLAB/Simulink and a comprehensive set of dedicated hardware (processor and I/O hardware).

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.

Gasoline Controlled Auto Ignition offers a high CO2 emission reduction potential, which is comparable to state-of-the-art, lean stratified operated gasoline engines. Contrary to the latter, GCAI low temperature combustion avoids NOX emissions, thereby trying to avoid extensive exhaust aftertreatment. The challenges remain in a restricted operation range due to combustion instabilities and a high sensitivity towards changing boundary conditions like ambient temperature, intake pressure or fuel properties. Once combustion shows instability, cyclic fluctuations are observed. These appear to have near-chaotic behavior but are characterized by a superposition of clearly deterministic and stochastic effects. Previous works show that the fluctuations can be predicted precisely when taking cycle-tocycle correlations into account. This work extends current approaches by focusing on additional dependencies within one single combustion cycle.

This paper describes challenges and possible solution of hybrid electrical vehicles test systems with a special focus on hardware-in-the-loop (HIL) test bench. The degree of novelty of this work can be seen in the fact that development and test of ECU for hybrid electrical powertrains can move more and more from mechanical test benches with real automotive components to HIL test systems. The challenging task in terms of electrical interface between an electric motor ECU and an HIL system and necessary real-time capable simulation models for electric machines have been investigated and partly solved. Even cell balancing strategies performed by battery management systems (BMU) can be developed and tested using HIL technology with battery simulation models and a precise cell voltage simulation on electrical level.

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.

Model-based development is the established way of developing embedded control algorithms, especially for safety-critical applications. The aim is to improve development efficiency and safety by developing the software at a high abstraction level (the model) and by generating the implementation (the C code) automatically from the model. Although model-based development focuses on the models themselves, downstream artifacts such as source code or executable object code have to be considered in the verification stage. Safety standards such as ISO 26262 require upper bounds to be determined for the required storage space or the execution time of real-time tasks, and the absence of run-time errors to be demonstrated. Static analysis tools are available which work at the code level and can prove the absence of such errors. However, the connection to the model level has to be explicitly established.

Hardware-in-the-Loop Simulation is a technology where the actual vehicles, engines or other components are replaced by a real-time simulation in a simulation computer, based on a mathematical model. That simulation reads ECU (Electronic Control Unit) output signals which would normally go to actuators. On the other hand the simulation must output the sensor signals which make the ECU ‘think’ it controls a real system. Generating these signals can be very difficult. Signals may be complex, depend on on-line computed variables, and be required to be output at high timing resolution. This paper describes the problems and presents a solution which employs high-performance Digital Signal Processors (DSP) to generate such signals on-line by Direct-Digital-Synthesis (DDS).