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The enactment of FMVSS 126 requires specific safety performance in vehicles 4,536 Kg (10,000 pounds) or less using an Electronic Stability Control (ESC) system as standard equipment by 2011. Further, in 2012, the regulation requires vehicles that have undergone aftermarket modification to remain in compliance with the performance standard. This paper describes: • a brief overview of the standard and its implications • the collaborative approach used in the first successful approach in meeting that requirement by a lift kit manufacturer o a Hardware In the Loop (HIL) test alternative for establishing a reasonable expectation for a vehicle to demonstrate compliance after modification. • Collaborative challenges overcome: o aftermarket manufacturers seeking information sharing with OEMs and Tier One suppliers: o respecting the intellectual property of OEMs and Tier One suppliers o maintaining the integrity between tool competitors and their customers in cross-collaborative efforts

Over the last few years the introduction of explicit system and software architecture models (e.g. AUTOSAR models) has led to changes in the automotive development process. The ability to simulate these models on a PC will be decisive for the acceptance of such approaches. This would support the early verification of distributed ECU and software systems and could therefore lead to cost savings. This paper describes an implementation of such an approach which fits into current development processes.

Model-based software development and automatic production code generation have become increasingly established in recent years. The aerospace industry and other industries, such as automotive, have 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 and improved quality due to more precise specifications, and early verification and validation by means of simulation. Model-based development is a general purpose development approach which can be applied to a wide variety of applications. Safety-critical systems, like found in aerospace applications to a large extent, but also found increasingly more often in other industries, like automotive or medical devices, pose special additional requirements to this process. This paper describes how model-based design and automatic production code generation can be applied to the development of safety-critical software.

This paper discusses our experiences on the implementation and benefits of using the Hardware-In-the-Loop (HIL) systems for Powertrain control system software verification and validation. The Visteon HIL system integrated with several off-the-shelf diagnostics and calibration tools is briefly explained. Further, discussions on test automation sequence control and failure insertion are outlined The capabilities and advantages of using HIL for unit level software testing, open loop and closed-loop system testing, fault insertion and test automation are described. HIL also facilitates Software and Hardware Interface validation testing with low-level driver and platform software. This paper attempts to show the experiences with and capabilities of these HIL systems.

The Controls and Software Engineering Team at BorgWarner Drivetrain Systems has successfully employed model-based software development for the past several years. Their drivetrain system control software, developed using MATLAB/Simulink/Stateflow, and autocoded using TargetLink, is on the road in many passenger vehicle applications. Using these tools, BorgWarner has realized the widely recognized benefits of model-based design; such as increased speed to market, improved quality, and reduced complexity. Validating algorithms early through simulation and rapid prototyping, then translating them to production software through automatic code generation has proven very successful for BorgWarner. When starting with model-based design, the BorgWarner team focused on developing the core application control algorithms in the modeling environment. Lower-level software such as I/O drivers, the task scheduler, and communication logic was still hand-coded.

It is not news anymore when somebody talks about increasing software content in today's vehicles, transportation systems and machinery. The software content and complexity has grown so tremendously and rapidly that even the most advanced product/software development techniques leave more to desire in view of evolving product life-cycles, feature content and need for development efficiency. Model-Based Design (MBD) techniques and V-Cycle based development processes address the significant need for managing complexity, and to some extent, efficiency in product development. Further efficiency in the development process can be achieved by enabling virtual validation of software components. The virtual validation environment for software not only has the ability to run the software component as a standalone unit for performance validation, but is also extended to the validation of the performance of the entire embedded software of an ECU, multiple ECUs and the entire system.

The Model-Based Development (MBD) process has been the key enabler of technical advancement. MBD helps manage complexity, while making product development faster by bringing clarity and transparency to the entire product development process, specifically software components. Developing software using MBD has required extensive, sophisticated toolchains, like the ones provided by dSPACE, that allow for efficient rapid controls prototyping, automatic code generation, and advanced validation and verification techniques with hardware-in-the-loop (HIL) test systems. MBD is an efficient iterative process that allows engineers to improve quality and deliver on demanding needs of product variants in the current competitive environment. However, the MBD process described commonly using the ‘V-Cycle’ diagram leads to the generation of large volumes of data artifacts and work products. The iterative process, variants and versions of these artifacts lead to even larger amounts of data.

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.

In the last few years, we have seen a tremendous increase in the rise in product complexity due to advances in technology and aircraft system functionality enhancement. The Model-based Design (MBD) process has helped manage the complexity of these systems while making product development faster by bringing more effective tools and methods to the entire process. Developing software using MBD has required extensive, sophisticated tool-chains that allow for efficient rapid controls prototyping, automatic code generation, and advanced validation and verification techniques using model-in-the-loop (MIL), software-in-the-loop (SIL), and hardware-in-the-loop (HIL) for both component testing and integration testing. However, the MBD process leads to generation of large volumes of data artifacts and work-products throughout the V-Cycle.