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The future worldwide emission regulations will request a drastic decrease of Diesel engine tailpipe emissions. Depending on the planned application and the real official regulations, a further strong decrease of engine out emissions is necessary, even though the utilized exhaust after-treatment systems are very powerful. To reduce NOx emissions internally, the external exhaust gas recirculation (EGR) is known as the most effective way. Due to the continuously increasing requirements regarding specific power, dynamic behavior and low emissions, future air path systems have to fulfill higher requirements and, consequently, become more and more complex, e.g. arrangements with a 2-stage turbo charging or 2-stage EGR system with different stages of cooling performance.

At the moment the documentation of failure inhibition matrices and the fault path management for different controller types and different vehicle projects are mainly maintained manually in individual Excel tables. This is not only time consuming but also gives a high potential for fault liability. In addition there is also no guarantee that the calibration of these failure inhibition matrices and its fault path really works. Conflicting aims between costs, time and fault liability require a new approach for the calibration, documentation and testing of failure inhibition matrices and the complete Diagnostic System Management (DSM) calibration. The standardization and harmonization of the Diagnostic System Management calibration for different calibration projects and derivates is the first step to reduce time and costs. Creating a master calibration for the conjoint fault paths and labels provides a significant reduction of efforts.

The modern engine development process is characterized by shorter development cycles and a reduced number of prototypes. However, simultaneously exhaust after-treatment and emission testing is becoming increasingly more sophisticated. It is expected that predictive simulation tools that encompass the entire powertrain can potentially improve the efficiency of the calibration process. The testing of an ECU using a HiL system requires a real-time model. Additionally, if the initial parameters of the ECU are to be defined and tested, the model has to be more accurate than is typical for ECU functional testing. It is possible to enhance the generalization capability of the simulation, with neuronal network sub-models embedded into the architecture of a physical model, while still maintaining real-time execution. This paper emphasizes the experimental investigation and physical modeling of the port fuel injected SI engine.

Future HD Diesel engine technology is facing a combination of both extremely low exhaust emission standards (US 2002/2004, EURO IV and later US 2007, EURO V) and new engine test procedures such as the European Transient Cycle (ETC) in Europe and the Not-to-Exceed Area (NTE) in the US). Customers furthermore require increased engine performance, improved efficiency, and long-term durability. In order to achieve all targets simultaneously, future HD Diesel engines must have improved fuel injection and combustion systems and utilize suitable technologies such as exhaust gas recirculation (EGR), variable geometry turbine turbocharger systems (VGT) and exhaust gas after-treatment systems. Future systems require precision controlled EGR in combination with a VGT-turbocharger during transient operation. This will require new strategies and calibration for the Electronic Engine Control Unit (ECU).

A calibration and validation workflow will be presented in this paper, which utilizes common static global models for fuel consumption, NOx and soot. Due to the applicability for warm-up tests, e.g. New European Driving Cycle (NEDC), the models need to predict the temperature influence and will be fitted with measuring data from a conditioned engine test bed. The applied model structure consisting of a number of global data-based sub-models is configured especially for the requirements of multi-injection strategies of common rail systems. Additionally common global models for several constant coolant water temperature levels are generated and the workflow tool supports the combination and segmentation of global nominal map with temperature correction maps for seamless and direct ECU setting.

HTOE (High Temperature Operation Endurance) and PTCE (Power Thermal Cycle Endurance) tests are typically performed according automotive group standards, such as LV 124 [1], VW80000 [2], FCA CS.00056 [3] or PSA B21 7130 [4]. The LV 124-2 group standard, composed by representatives of automobile manufacturers like Audi AG, BMW AG, Volkswagen AG and Porsche AG describes a wide range of environmental tests and their requirements. In addition, calculation parameters and a method are given in the standard. These group standard tests are often attributed to IEC 60068-2-2 [5] for HTOE and IEC 60068-2-14 [6] for PTCE. As both of these tests are typically of long duration, fundamentally linked to reliability (therefore requiring a statistically significant number of samples) and of considerable importance to power electronic, they are worthy of additional scrutiny for automotive developers as most automotive development moves towards electrification.

Actual automotive themes in the beginning century are globalization and platform concepts. Platforms reduce manpower for basic power train development and enable a higher vehicle quality by sharing development cost to many models. New drive train generations with direct injected diesel and gasoline engines, variable valve train systems and hybrid drives require complex electronic control systems with many control parameters, which must be calibrated for each platform model to fulfill the targets for emissions, diagnostics and driveability. Calibration becomes a critical procedure in vehicle development. A negative effect of the platform is the reduced possibility to give a model or an OEM a brand specific driveability character, traditionally an important sales - promoting factor. The paper describes a tool for the objective real time assessment of vehicle driveability and vehicle character, using a new subjective - objective approach.

Originally developed for the automotive market, a fully automatic real-time measurement tool AVL-DRIVE is commercially available for analyzing and scoring vehicle drive quality, also known as “Driveability”. This system from AVL uses its own transducers, calibrated to the sensitivity and response of the human body to measure the forces felt by the driver, such as acceleration, shock, surging, vibration, noise, etc. Simultaneously, the vehicle operating conditions are measured, (throttle grip angle, engine speed, gear, vehicle speed, temperature, etc.). Because the software is pre-programmed with the scores from a multitude of different vehicles in each vehicle class via neural networks and fuzzy logic formula, a quality score with reference to similar competitor vehicles is instantly given. This tool is already successfully implemented in the market for years to investigate such driveability parameters for passenger cars.

Enhanced octane is one route to fuels differentiation where associated vehicle performance benefits are generally measured under controlled wide-open throttle tests on a chassis dynamometer. The combined availabilities of relevant ECU data via OBD and telematic loggers present new opportunities to assess such fuel benefits on the road in normal real-world driving environments. A novel methodology is described in this paper which utilised the remote logging of key engine EOBD data from a fleet trial and the results successfully demonstrated significant octane-derived benefits in many vehicles throughout normal mixed-roads driving. The availability and the reliability of telematic loggers mean that the method could be implemented in a scalable way as a complementary approach in addition to conventional laboratory vehicle testing.

This paper gives insights in the theoretical measurement uncertainty of E-Drive rotor position dependent results, like Id and Iq calculations, done by a modern propulsion power analyzer (PA). The calculation of Id and Iqis fundamental to perform control optimization and application tasks for an E-Drive system. To optimize the E-Drive system application towards e.g., best efficiency, best performance, or improved NVH the importance of the testing toolchain is described: a power analyzer delivering the required results, an automation system, and a Design of Experiment tool to set improved target values. Consequently, inverters applications featuring field-oriented control (FOC) with permanent magnet synchronous machines (PMSM) are updated with a chosen control strategy. For achieving a certain behavior of an E-Drive, different degrees of freedom in the Inverter Control Unit are available; Lookup tables Id and Iq represent two fundamental application labels to be considered.