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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.

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.

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.

Hardware-in-the-loop (HIL) simulation is now a standard component in the vehicle development process as a method for testing electronic control unit (ECU) software. HIL simulation is used for all aspects of development, naturally including safety-relevant functions and systems. This applies to all test tasks (from function testing to release tests, testing a single ECU or an ECU network, and so on) and also to different vehicle domains: The drivetrain, vehicle dynamics, driver assistance systems, interior/comfort systems and infotainment are all tested by HIL simulation. At the same time, modern vehicles feature more and more safety-related systems such as Adaptive Cruise Control, Electronic Stability Program, Power Assisted Steering, and Integrated Chassis Management.

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.

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 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).

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.