Search Results

Current developments in automotive industry such as hybrid powertrains and the continuously increasing demands on emission control systems, are pushing complexity still further. Validation of such systems lead to a huge amount of test cases and hence extreme testing efforts on the road. At the same time the pressure to reduce costs and minimize development time is creating challenging boundaries on development teams. Therefore, it is of utmost importance to utilize testing and validation prototypes in the most efficient way. It is necessary to apply high levels of instrumentation and collect as much data as possible. And a streamlined data pipeline allows the fleet managers to get new insights from the raw data and control the validation vehicles as well as the development team in the most efficient way. In this paper we will demonstrate a data-driven approach for validation testing.

In spark-ignition engines, fluctuations of the in-cylinder pressure trace and the apparent rate of heat release are usually observed from one cycle to another. These Cycle-to-Cycle Variations (CCV) are affected by the early flame development and the subsequent flame front propagation. The CCV are responsible for engine performance (e.g. fuel consumption) and the knock behavior. The occurrence of the phenomena is unpredictable and the stochastic nature offers challenges in the optimization of engine control strategies. In the present work, CCV are analyzed in terms of their impact on the engine knock behavior and the related efficiency. Target is to estimate the possible fuel consumption savings in steady-state operation and in the drivecycle, when CCV are reduced. Since CCV are immanent on real engines, such a study can only be done by means of simulation.

In the present work, a scalable simulation methodology is presented that enables the assessment of the impact of SI-engine cycle-to-cycle combustion variations on fuel consumption and hence CO2 emissions on three different levels of modeling depth: in-cylinder, steady-state engine and transient engine and vehicle simulation. On the detailed engine combustion chamber level, a 3D-CFD approach is used to study the impact of the turbulent in-cylinder flow on the cycle-resolved flame propagation characteristics. On engine level, cycle-to-cycle combustion variations are assessed regarding their impact on indicated mean effective pressure, aiming at estimating the possible fuel consumption savings when cyclic variations are minimized. Finally, on the vehicle system level, a combined real-time engine approach with crank-angle resolved cylinder is used to assess the potential fuel consumption savings for different vehicle drivecycle conditions.

In order to meet current and future emission and CO2 targets, an efficient vehicle thermal management system is one of the key factors in conventional as well as in electrified powertrains. Global vehicle simulation is already a well-established tool to support the vehicle development process. In contrast to conventional vehicles, electrified powertrains offer an additional challenge to the thermal conditioning: the durability of E-components is not only influenced by temperature peaks but also by the duration and amplitude of temperature swings as well as temperature gradients within the components during their lifetime. Keeping all components always at the preferred lowest temperature level to avoid ageing under any conditions (driving, parking, etc.) will result in very high energy consumption which is in contradiction to the efficiency targets.

At first glance RDE seems to be a road testing topic only, mistakenly. While Type approval test must be performed at the Road and Chassis Dyno, development work beforehand delivers solutions fulfilling the demanded legislation limits. Making the right development steps and decisions will lead to a technical solution within economy of scales. Much of this work done happens on engine testbeds and Real Driving Emissions (RDE) per UN-ECE legislation or the new test cycle for the chassis dyno according WLTP (Worldwide Harmonized Light-Duty Test Procedure) will not change that. The question is, are engine test beds fit for this new challenge or are changes required? One characteristic element of RDE is the randomness of operating conditions generated by a road drive. There must be found a way, to achieve RDE relevant test conditions in a most reproducible manner.

Future demands regarding emissions, fuel consumption and driveability lead to complex engine and power train control systems. The calibration of the increasing number of free parameters in the ECU's contradicts the demand for reduced time in the power train development cycle. This paper will focus on the automatic, unmanned closed loop optimization of driveability quality on a high dynamic engine test bed. The collaboration of three advanced methods will be presented: Objective real time driveability assessment, to predict the expected feelings of the buyers of the car Automatic computer assisted variation of ECU parameters on the basis of statistical methods like design of experiments (DoE). Thus data are measured in an automated process allowing an optimization based on models (e.g. neural networks).

Validation of highly automated or autonomous vehicles is nowadays still a major challenge for the automotive industry. Furthermore, the homologation of ADAS/AD vehicles according to global regulations is getting more essential for their safe development and deployment around the world. In order to assure that the autonomous driving function is able to cope with the huge number of possible situations during operation, comprehensive testing of the functions is required. However, conventional testing approaches such as driving distance-based validation approach in the real world, can be time- and cost-consuming. Therefore, a scenario-based virtual validation and testing method is considered to be a proper solution. In this paper, we propose a virtual assessment framework using a fully automated test case generation method. This framework is embedded into the continuous development and validation process.

Approaching engineering limits for the thermal design of battery modules requires virtual prototyping and appropriate models with respect to physical depth and computational effort. A multi-scale and multi-domain model describes the electrochemical behavior of a single battery unit cell in 1D+1D at the level of intra-cell phenomena, and it applies a 3D thermal model at module level. Both models are connected within a common vehicle simulation platform. The models are discussed with special emphasis on battery degradation such as solid electrolyte interphase layer formation, decomposition and lithium plating. The performance of the electrochemical model is assessed by discharge cycles and repeated charge/discharge simulations. The thermal module model is compared to CFD reference data and studied with respect to its grid sensitivity.

The present work introduces an innovative mechanistically based 0D spray model which is coupled to a combustion model on the basis of an advanced mixture controlled combustion approach. The model calculates the rate of heat release based on the injection rate profile and the in-cylinder state. The air/fuel distribution in the spray is predicted based on momentum conservation by applying first principles. On the basis of the 2-zone cylinder framework, NOx emissions are calculated by the Zeldovich mechanism. The combustion and emission models are calibrated and validated with a series of dedicated test bed data specifically revealing its capability of describing the impact of variations of EGR, injection timing, and injection pressure. A model based optimization is carried out, aiming at an optimum trade-off between fuel consumption and engine-out emissions. The findings serve to estimate an economic optimum point in the NOx/BSFC trade-off.

The present work introduces a fully integrated real-time (RT) capable engine and vehicle model. The gas path and drive line are described in the time domain of seconds whereas the reciprocating characteristics of an IC engine are reflected by a crank angle resolved cylinder model. The RT engine model is derived from a high fidelity 1D cycle simulation and gas exchange model to support an efficient and consistent transfer of model data like geometries, heat transfer or combustion. The workflow of model calibration and application is outlined and base ECU functionalities for boost pressure, EGR, smoke and idle speed control are applied for transient engine operation. Steady state results of the RT engine model are compared to experimental data and 1D high fidelity simulations for 19 different engine load points. In addition an NEDC (New European Drive Cycle) is simulated and results are evaluated with data from chassis dynamometer measurements.

Combustion of premixed stoichiometric charge is free of soot particle formation. Consequently, the development of direct injection (DI) spark ignition (SI) engines aims at providing premixed charge to avoid or minimize soot formation in order to meet particle emissions targets. Engine development methods not only need precise engine-out particle measurement instrumentation but also sensors and measurement techniques which enable identification of in-cylinder soot formation sources under all relevant engine test conditions. Such identification is made possible by recording flame radiation signals and with analysis of such signals for premixed and diffusion flame signatures. This paper presents measurement techniques and analysis methods under normal engine and vehicle test procedures to minimize sooting combustion modes in transient engine operation.

Today's powertrains are becoming more and more complex due to the increasing number of gear box types requiring gearshift patterns like conventional (equipped with GSI) and automatic-manual transmissions (AT, AMT), double clutch and continuous variable transmissions (DCT, CVT). This increasing variety of gear boxes requires a higher effort for the overall optimization of the powertrain. At the same time, it is necessary to assess the impact of different powertrains and control strategies on CO₂ emissions very early in the development process. The optimization of Gear Shift Patterns (G.S.P.) has to fulfill multiple constraints in terms of objective customers' requirements, like driveability, NVH, performance, emissions and fuel consumption. For these reasons, RENAULT and AVL entered an engineering collaboration in order to develop a dedicated simulation tool: CRUISE GSP.

Future legislation scenarios as well as stringent CO2 targets, in particular under real driving conditions, will require the introduction of new and additional powertrain technologies. Beside the increasing electrification of the powertrain, it will be essential to utilize the full potential of the Internal Combustion Engine (ICE). There is clearly a competition of new and different ICE-Technologies [1] including VCR. VCR systems are expected to be introduced to a considerable number of next generation turbocharged Spark Ignited (SI) engines in certain vehicle classes. The implementation of Miller or Atkinson cycles is an essential criterion for increased geometric Compression Ratio (CR). The DUAL MODE Variable Compression System (VCS)TM enables a 2-stage variation of the connecting rod length and thus of the compression ratio (CR).

Dynamometer (dyno) durability testing plays a significant role in reliability and durability assessment of commercial engines. Frequently, durability test procedures are based on warranty history and corresponding component failure modes. Evolution of engine designs, operating conditions, electronic control features, and diagnostic limits have created challenges to historical-based testing approaches. A physics-based methodology, known as Load Matrix, is described to counteract these challenges. The technique, developed by AVL, is based on damage factor models for subsystem and component failure modes (e.g. fatigue, wear, degradation, deposits) and knowledge of customer duty cycles. By correlating dyno test to field conditions in quantifiable terms, such as customer equivalent miles, more effective and efficient durability test suites and test procedures can be utilized. To this end, application of Load Matrix to a heavy-duty diesel engine is presented.

In recent years, the use of high-power inverters has become increasingly prevalent in vehicles applications. With the increasing number of electric vehicle models comes the need for efficient and reliable testing methods to ensure the proper functioning of these inverters. One such method is the use of Hardware-in-the-Loop (HiL) environments, where the inverter is connected to a simulated environment to test its performance under various operating conditions. HiL testing allows for faster and more cost-effective testing than traditional methods and provides a safe environment to evaluate the inverter's response to different scenarios. Further, in such an environment, it is possible to specifically stimulate those system states in which conflicts between the lines arise regarding the ideal system parametrization. By combining HiL testing with design-of-experiments and modelling methods, the propulsion system can hence be optimized in a holistic manner.

Increasing requirements for the result quality of exhaust emission analyzers and state of the art analyzer technology require a new point of view regarding measuring range definitions and linearization procedures. To make best use of the power of this analyzer technology, linearization procedures need reconsideration. In certification laboratories, legislation defines the procedures to linearize an exhaust emission analyzer more or less stringently. On the other hand, on testbeds for development purposes there are many possibilities for making use of today's improved analyzers. However, procedures are often used in development labs that are very similar to those mentioned in the legislation. For some measurement purposes it is necessary to leave these procedures regarding measuring ranges and their specifications behind. The exhaust gas analyzing system has to provide consistent result quality during the whole test procedure.

Fuel consumption is the most important contributor to the total cost of ownership for mass produced motorcycles. Therefore, best fuel economy is one main influencing criteria for a decision to purchase motorcycles. Furthermore, increasingly stringent emission legislations limit and additional OBD requirements must be fulfilled. A new combined test approach has been developed that minimizes accuracy losses in the development process which compensates for the variability of driving behavior in the chassis dyno environment. An engine testbed combined with a belt drive transmission enables operation in single engine or in Powerpack (i.e. internal combustion engine including transmission) configuration as well as under steady state or dynamic operating mode. Since the belt drive transmission is integrated in the test rig, realistic inertia situation for the single engine operating test configuration is ensured.

System lubrication in automotive powertrains is a growing topic for development engineers. Hybrid and pure combustion system complexity increases in search of improved efficiency and better control strategy, increasing the number of components with lubrication demand and the interplay between them, while fully electric systems drive for higher input speeds to increase e-motor efficiency, increasing bearing and gear feed rate demands. Added to this, many e-axle and hybrid systems are in development with a shared medium and circuit for e-motor cooling and transmission lubrication. Through all this, the lubricant forms a common thread and is a fundamental component in the system, but no standardized tests can provide a suitable methodology to investigate the adequate lubrication of components at powertrain level, to support the final planned vehicle usage.

In 2017 the European authorities put into effect the first part of a new certification test procedure for Real Driving Emissions (RDE). Similar tests are planned in other regions of the world, such as the upcoming China 6a/6b standards, further tightening emission limits, and also the introduction of RDE tests. Both restrictions pose challenging engineering tasks for upcoming vehicles. RDE certification tests feature significantly more demanding engine operating conditions and thus, emit more pollutants by orders of magnitude compared to known cycles like NEDC. Here, especially the reduction of NOx is a specific technical challenge, as it needs to compromise also with reduction targets on carbon dioxide. The fulfilment of both emission limits requires a widening of the focus from an isolated engine or exhaust aftertreatment view to a system engineering view involving all hardware and software domains of the vehicle.

This work presents a physical model that calculates the efficiency maps of the inverter-fed Permanent Magnet Synchronous Machine (PMSM) drive. The corresponding electrical machine and its controller are implemented based on the two-phase (d-q) equivalent circuits that take into account the copper loss as well as the iron loss of the PMSM. A control strategy that optimizes the machine efficiency is applied in the controller to maximize the possible output torque. In addition, the model applies an analytical method to predict the losses of the voltage source inverter. Consequently, the efficiency maps within the entire operating region of the PMSM drive can be derived from the simulation results, and they are used to represent electric drives in the system simulation model of electric vehicles (EVs).