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The complexity of automobile powertrains grows continuously. At the same time, development time and budget are limited. Shifting development tasks to earlier phases (frontloading) increases the efficiency by utilizing test benches instead of prototype vehicles (road-to-rig approach). Early system verification of powertrain components requires a closed-loop coupling to real-time simulation models, comparable to hardware-in-the-loop testing (HiL). The international research project Advanced Co-Simulation Open System Architecture (ACOSAR) has the goal to develop a non-proprietary communication architecture between real-time and non-real-time systems in order to speed up the commissioning process and to decrease the monetary effort for testing and validation. One major outcome will be a generic interface for coupling different simulation tools and real-time systems (e.g. HiL simulators or test benches).

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.

Today, hardware-in-the-loop (HIL) simulation is common practice as a testing methodology for electronic control units (ECUs). An essential criterion for the efficiency of an HIL system is the availability of powerful test automation having access to all of its hardware and software components (including I/O channels, failure insertion units, bus communication controllers and diagnostic interfaces). The growing complexity of vehicle embedded systems, which are interconnected by bus systems (like CAN, LIN or FlexRay), result in hundreds or even thousands of tests that have to be done to ensure the correct system functionality. This is best achieved by automated testing. Automated testing usually is performed by executing tests on a standard PC, which is interconnected to the HIL system. However, higher demands regarding timing precision are hard to accomplish. As an example, ECU interaction has to be captured and responded to in the range of milliseconds.

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.

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.

Validating control units with hardware-in-the-loop (HIL) simulators is an established method for quality enhancements in automotive software. It is primarily used for testing applications, but in view of increased networking between electronic control units, it can also be used for testing communication scenarios. The testing of electronic control unit (ECU) communication often includes only positive testing. Simple communication nodes are used for this, and communication analyzers are used for verifying communication up to the physical level. However, it is not only an ECU's positive communication behavior that has to be tested, but also its correct behavior in the event of communication errors. In HIL communication scenarios, it is not only possible to emulate the missing bus nodes (restbus simulation) with a link to real-time signals; correct ECU behavior in the event of communication errors can also be tested.

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) testing is used by commercial vehicle original equipment manufacturers (OEMs) in several fields of electronics development. HIL tests are a part of the standard development process for engine and machine control systems. For electronic control units (ECUs), not only the HIL test of the hardware but also the controller software validation is very important. For hardware diagnostics validation, a dynamic simulation of the real system could be omitted and an open-loop test of the controller is sufficient in most cases. For most controller software validation including OBD (on-board diagnosis) tests, detailed but real-time capable models have to be used. This article describes the needs and challenges of models in hardware-in-the-loop (HIL) based testing, taking into account the wide range of commercial and off-highway vehicles.

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).

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.

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.

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.

The essential task of a battery management system (BMS) is to consistently operate the high-voltage battery in an optimum range. Due to the safety-critical nature of its components, prior testing of a BMS is absolutely necessary. Hardware-in-the-loop (HIL) simulation is a cost-effective and efficient tool for this. Testing the BMS on a HIL test bench requires an electronics unit to simulate the cell voltages and a scalable real-time battery model. This paper describes a HIL system that enables comprehensive testing of BMS components. Hardware and software solutions are proposed for the high requirements of these tests. The individual components are combined to make a modular system, and safety-critical aspects are examined. The paper shows that the system as developed fulfills all the requirements derived from the different test scenarios for BMS systems.

Embedded software in the car is becoming increasingly complex due to the growing number of software-based controller functions and the increasing complexity of the software itself. Model-based development with Simulink combined with TargetLink for automatic code generation helps significantly to improve the quality of the embedded software. The development of large-scale Simulink models in distributed teams is a challenging task, especially when developing safety-critical software that must fulfill requirements stated in the ISO 26262 [1] safety standard. In practice, many questions on how to avoid the pitfalls of distributed model-based development remain open, such as how to define an appropriate model architecture, handle model complexity, and achieve compliance with ISO 26262. The intent of this paper is threefold. Firstly, we summarize those requirements of ISO 26262 that are relevant for developing complex software in a distributed environment.

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).

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.