Powertrain Instrumentation and Test Systems

The major societal challenges have significant effect on how the automotive industry is evolving. Automotive CO2 emissions contribute to global warming. OEMs are addressing such requirements by implementing downsizing concepts, electric mobility (particularly in megacities), hybrid powertrain concepts or by employing alternative energy resources (e.g. bio-fuels) or electric vehicles with hydrogen fuel cells. Growing urbanization is leading to bigger and bigger cities. With space being one of the most valuable resources in rapidly expanding megacities, new concepts are required to ensure the continuation of individual mobility. Therefore automakers are developing self-parking systems, automatic cruise control technologies up to fully automated vehicles. The growing vehicle density, coupled with a rising proportion of aging people, is leading to a hugely increased risk of traffic accidents. Again, the automotive industry is responding by offering innovative ADAS functions. This growing pressure to innovate together with the demand for shorter development cycles, along with new statutory rules, require changes in the powertrain development methodology. As a result, there are shifts in the tasks of test bed systems as simulation and real component testing merge more and more.

Different test bed configurations are used in the development of advanced powertrains in automotive engineering. Internal combustion engine test beds are still very important testing components. Its further development accounts for a substantial amount of R&D effort in present-day vehicles. An increasing number of other powertrain components (as batteries, eMotors, transmissions, fuel cell systems, power electronics, etc.) in modern automotive powertrains requires many other test bed types. All of them deliver also valuable data for validating and calibrating simulation models of such single components. An ever-increasing share of the development budget for modern vehicles is being invested in the development of a great variety of control units. Such control units contribute substantially toward making our vehicles more environmentally friendly, comfortable and safe. The verification and validation test facilities for these control unit test beds are called hardware-in-the-loop or HiL test beds. Test of the full functionality of powertrains after integrating multiple components into a complete system is accomplished either on powertrain test beds or on chassis dynamometer test systems before starting the final test on the road.

Given their high investment costs, it is paramount that test beds have to be operated with maximum efficiency. This requirement results in the need for test beds with modular design. A test bed composed of standardized modules is easily expandable because, due to economies of scale, standardized modules are available at much lower cost than testing systems built for specific projects. As a test bed comprises a multitude of different hardware modules, we have called this chapter Hardware Perspective. The hardware components measure the required variables in the unit under test(s) and supply them to the automation system. Hardware components (actuators or stimuli), in turn, transfer the set values from the automation system back to the unit under test. This process is supported by the two bottom layers of a modular test bed design —the physical level and the connection level. The first layer comprises sensors and actuators as well as intelligent systems for measuring the many different variables needed in the development process. The second layer connects these systems to the automation system layer via bus systems, analog connections or PC interfaces.

Different software functions are needed to automatically execute a variety of testing tasks. They range from functions as automatic data acquisition, calculation of formulae, generating set value traces for different actuators, monitoring various conditions up to components that ensure the unit under tests’ safety. Important are also functions that simulate components that are not physically present on the test bed but still affect the actual behavior of the physical components under test. In one form or another, most of these functions are present in test automation systems used in the automotive industry. Stable and robust software structures of test bed automation systems often take advantage of interface standards. The use of standards allows users to add new software components to an automation system without changing the already available system and tackle new testing challenges in a fast and cost-efficient way.

Stable and robust software structures of test bed automation systems often take advantage of interface standards. The use of standards allows users to add new software components to an automation system without changing the already available system and tackle new testing challenges in a fast and cost-efficient way.

Globalization has continued steadily over recent years, intensifying the competition among automakers even further. This has had a direct impact on the test facilities, which, likewise, have to be prepared to respond to the changing framework conditions with great speed and efficiency. As a result of this trend, test facilities today are increasingly being used globally, requiring the necessary support through suitable solutions. Sophisticated software solutions have also led to a steady increase in the degree of automation in testing operation. Many managers see the vision of fully automated test facilities with maximum utilization—also on a global scale—as a matter of the (near) future. The ability to handle the growing test complexity, combined with maximally utilized test beds, is a key factor of success for future test facilities. Therefore this chapter deals with the architectural layer of test facility-wide data processing. Accordingly, the goal in this layer is to analyze and optimize not only logistics processes, such as regular quality assurance management for measuring equipment, but also matters pertaining to test facility capacity management. The layer additionally provides support to development teams all over the world by standardizing the ways they access data (measuring results or control unit parameters).