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State-of-the-art powertrain concepts with automatic transmission must comply with increasingly stringent legislation on emissions and fuel consumption while fulfilling or surpassing customers' expectations as to driveability. In this respect, automated manual transmissions (AMT) and automated shift transmissions (AST) must compete with conventional automatic transmissions (AT) and continuously variable transmissions (CVT). In order to exploit the theoretical advantages of ASTs and put them into practice, complex ECU functions are needed to coordinate engine and transmission. Adaptive control, sophisticated clutch management and an intelligent shifting strategy allow shifting quality and shifting points to be simultaneously optimized to the effect that performance and comfort are increased while fuel consumption is reduced.

IAV GmbH is currently developing a test case generator, which uses information from Simulink®/Stateflow® models to generate test cases automatically. These test cases can then be applied during software tests for an ECU to show conformance to the original model. Using predefined rules, test cases for individual blocks are generated and converted into test cases for a whole model. The test cases can be saved as a XML file. Then, this file can be converted into test script languages which are used by tools for test execution. With the test case generator, the time-consuming and error-prone task of manual test case definition can be automated, thus decreasing test expenses for each test while increasing test quality.

Global warming is a climate phenomenon with world-wide ecological, economic and social impact which calls for strong measures in reducing automotive fuel consumption and thus CO2 emissions. In this regard, turbocharging and the associated designing of the air path of the engine are key technologies in elaborating more efficient and downsized engines. Engine performance simulation or development, parameterization and testing of model-based air path control strategies require adequate performance maps characterizing the working behavior of turbochargers. The working behavior is typically identified on test rig which is expensive in terms of costs and time required. Hence, the objective of the research project “virtual Exhaust Gas Turbocharger” (vEGTC) is an alternative approach which considers a physical modeled vEGTC to allow a founded prediction of efficiency, pressure rise as well as pressure losses of an arbitrary turbocharger with known geometry.

Conventional methods of physicochemical models require various experts and a high measurement demand to achieve the required model accuracy. With an additional request for faster development time for diagnostic algorithms, this method has reached the limits of economic feasibility. Machine learning algorithms are getting more popular in order to achieve a high model accuracy with an appropriate economical effort and allow to describe complex problems using statistical methods. An important point is the independence from other modelled variables and the exclusive use of sensor data and actuator settings. The concept has already been successfully proven in the field of modelling for exhaust gas aftertreatment sensors. An engine-out nitrogen oxide (NOX) emission sensor model based on polynomial regression was developed, trained, and transferred onto a conventional automotive electronic control unit (ECU) and also proves real-time capability.

A promising combustion technology for DISI downsizing engines is the Miller cycle. It is based on an early intake valve closing for the separation of effective and geometric compression ratio. Therefore IAV has prepared a turbocharged DISI test engine with a high geometric compression ratio. This engine is equipped with the Schaeffler “UniAir” variable valve train in order to investigate a variable Miller cycle valve timing in the turbocharged map area. The goal is to investigate whether and how a rapidly variable Miller cycle can influence the knocking behavior. Therefore its potential for a SI knock control can be evaluated. The investigated parameters in a steady-state engine dyno mode were the intake valve closing timing, the intake camshaft phasing and the ignition timing. A variable intake valve closing Miller cycle strategy, a variable intake camshaft phasing Miller cycle strategy and a state-of-the- art ignition timing strategy have been investigated.

To meet the targets of Indian future emission legislation, an electrification and automation of today’s manual transmission technology is necessary. For this reason, IAV invented an electrified automated transmission family, based on well-known manual transmission technology. This low-cost automated manual transmission (AMT) approach is equipped with a 48 V electric machine and can be used as pure electric or hybrid drivetrain. Furthermore, it is possible to realize power shifts by using just one dry friction element. A small number of standard components combined with a low voltage electric machine and an electromechanical actuation system is sufficient to create a maximum of flexibility to meet future emission fleet targets, without having the disadvantageous high costs for a high-voltage electric system. To detect the optimal powertrain configuration, IAV used a unique advance development tool called Powertrain Synthesis.

A physics-based simulation program developed by IAV is used to calibrate the torque structure and cylinder charge calculation in the electronic control unit of SI engines. The model calculates both the charge cycle and combustion phase based on flow mechanics and a fractal combustion model. Once the air mass in the charge cycle has been computed, a fractal combustion model is used for the ongoing calculation of cylinder pressure and temperature. The progression of cylinder pressure over the high and low-pressure phases also provides information on engine torque. Following the engine-specific calibration of the model using elemental geometric information and reduced test bench measurements, the physical engine properties can be simulated over the operating cycle. The calibrated model allows simulations to be carried out at all operating points and the results to be treated as virtual test bench measurements.

The software design of this new engine control unit is based on a unique and homogenous torque structure. All input signals are converted into torque equivalents and a torque coordinator determines their influence on the final torque delivered to the powertrain. The basic torque structure is independent on the type of fuel and can be used for gasoline, diesel, or CNG injection systems. This allows better use of custom specific algorithms and facilitates reusability, which is supported by the graphical design tool that creates all modules using automatic code generation. Injection specific algorithms can be linked to the software by simply setting a software switch.