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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.

The safety of BEVs in driving, charging and parking condition is essential for the success of electrification in automotive industry as well as key driver of any future development of Li-Ion HV battery. AVL has developed a unique simulation approach in which the multi-physical behavior of the single cell in thermal runaway is modelled and applied to module, pack or vehicle level. In addition and beside this cell behavior, various more physical phenomena during thermal propagation on pack level are considered and predicted by the simulation method: component melting, ignition and flammibilty of venting gas and HV failures.

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.

With the increased number of variants, the preservation of a brand-specific vehicle DNA becomes more and more important. Paired with growing customer expectations, brand DNA can be a crucial point in the decision-making process of buying a new vehicle. Whereas the customer will assess the DNA subjectively during driving by evaluating the vehicle drive quality (“driveability”), most manufacturers are not merely relying on subjective evaluations by having test drivers perform maneuvers with prototype vehicles. Nowadays, the assessment is performed objectively during the vehicle development process. As a supporting measure, the Anstalt für Verbrennungskraftmaschinen List (AVL) has made the objective assessment tool AVL-DRIVE commercially available. Up to now, the AVL-DRIVE ratings had to be manually analyzed and checked for outliers. Low ratings and high deviations to a priori specified target values are a good starting point for the search of outliers.

A TGDI (turbocharged gasoline direct injection) engine is developed to realize both excellent fuel economy and high dynamic performance to guarantee fun-to-drive. In order to achieve this target, it is of great importance to develop a superior combustion system for the target engine. In this study, CFD simulation analysis, steady flow test and transparent engine test investigation are extensively conducted to ensure efficient and effective design. One dimensional thermodynamic simulation is firstly conducted to optimize controlling parameters for each representative engine operating condition, and the results serve as the input and boundary condition for the subsequent Three-dimensional CFD simulation. 3D CFD simulation is carried out to guide intake port design, which is then measured and verified on steady flow test bench.

Local air pollution, noise emissions as well as global CO2 reduction and public pressure drive the need for zero emission transport solutions in urban areas. OEMs are currently developing battery electric vehicles with the focus to provide emission free urban transportation combined with lowest total cost of ownership and consequently a positive business case for the end customers. Thereby the main challenges are electric range, product cost, system weight, vehicle packaging and durability. Hence they are the main drivers in current developments. In this paper AVL describes two of its truck and bus solutions - a modular battery concept as well as a concept for an integrated electric axle. Based on the vehicle requirements concept designs for both systems are presented.

Increasing powertrain complexity and the growing number of vehicle variants are putting a strain on current calibration development processes. This is particularly challenging for vehicle drivability calibration, which is traditionally completed late in the development cycle, only after mature vehicle hardware is available. Model-based calibration enables a shift in development tasks from the real world to the virtual world, allowing for increased system robustness while reducing development costs and time. A unique approach for drivability calibration was developed by incorporating drivability analysis software with online optimization software into a virtual engine test cell environment. Real-time, physics-based engine and vehicle simulation models were coupled with real engine controller hardware and software to execute automated drivability calibration within this environment.

Best fuel efficiency is one of the core requirements for commercial vehicles in India. Consequently it is a central challenge for commercial vehicle OEMs to optimize the entire powertrain, hence match engine, transmission and rear axle specifications best to the defined application. The very specific real world driving conditions in India (e.g. traffic situations, road conditions, driver behavior, etc.) and the large number of possible commercial powertrain combinations request an efficient and effective development methodology. This paper presents a methodology and tool chain to specify and develop commercial powertrains in a most efficient and effective way. The methodology is based on the measurement of real world driving scenarios, identification of representative Real World Driving Profiles and vehicle system simulation which allows extended analysis of the road topography, the traffic situation as well as the driver behavior.

This paper describes a method for optimization of engine settings in view of best total cost of operation fluids. Under specific legal NOX tailpipe emissions requirements the engine out NOX can be matched to the current achievable SCR NOX conversion efficiency. In view of a heavy duty long haul truck application various specific engine operation modes are defined. A heavy duty diesel engine was calibrated for all operation modes in an engine test cell. The characteristics of engine operation are demonstrated in different transient test cycles. Optimum engine operation mode (EOM) selection strategies between individual engine operation modes are discussed in view of legal test cycles and real world driving cycles which have been derived from on-road tests.

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.

The reduction of CO₂ emissions represents a major goal of governments worldwide. In developed countries, approximately 20% of the CO₂ emissions originate from transport, one third of this from commercial vehicles. CO₂ emission legislation is in place for passenger cars in a number of major markets. For commercial vehicles such legislation was also already partly published or is under discussion. Furthermore the commercial vehicles market is very cost sensitive. Thus the major share of fuel cost in the total cost of ownership of commercial vehicles was already in the past a major driver for the development of efficient drivetrain solutions. These aspects make the use of new powertrain technologies, specifically hybridization, mandatory for future commercial powertrains. While some technologies offer a greater potential for CO₂ reduction than others, they might not represent the overall optimum with regard to the total cost of ownership.

Alternative fuels, especially fuels based on biological matter, are gaining more and more attention. Not only as a pure substitute of oil but also in terms of a possibility for further reduction in emission and as an option to improve the global CO2 balance. For improving the engine performance (emissions, fuel consumption, torque and drivability) the adjustment of fuel injection, the fuel evaporation process and the combustion process itself is paramount. In order to exploit the full potential of alternative fuels excellent knowledge of the fuel properties, including the impact on ignition and flame propagation, is required. This needs suitable tools for analysis of the fuel injection and combustion process. These tools have to support the optimization of the combustion system and the dynamic engine calibration for lowest emissions and most efficient use of fuel. As the term “Alternative Fuels” covers a very wide area a brief overview on available fuel types will be made.

Design of cylinder heads involves complex constraints that must satisfy thermal, strength, performance, and manufacturing requirements which present a great challenge for successful development. During development of a new highly loaded cylinder head, CAE methods predicted unacceptable fatigue safety factors for the initial prototype design. Hydropulsator component testing was undertaken and the results were correlated with the analysis predictions using a statistical method to calculate failure probability. Shape optimization was undertaken to improve high cycle fatigue safety in vulnerable regions of the cylinder head water jacket for the subsequent design release. The optimization process provided more efficient design guidance than previously discovered through a traditional iterative approach. Follow-on investigations examined other shape optimization software for fatigue improvement in the cylinder head.

This paper describes the development and achievement of a target engine sound for a V6 SUV in consideration of the sound quality preferences of customers in the U.S. First, a simple definition for engine sound under acceleration was found using order arrangement, frequency balance, and linearity. These elements are the product of commonly used characteristics in conventional development and can be applied simply when setting component targets. The development focused on order arrangement as the most important of these elements, and sounds with and without integer orders were selected as target candidates. Next, subjective auditory evaluations were performed in the U.S. using digitally processed sounds and an evaluation panel comprising roughly 40 subjects. The target sound was determined after classifying the results of this evaluation using cluster analysis.

The OBD II and EOBD legislation have significantly increased the number of system components that have to be monitored in order to avoid emissions degradation. Consequently, the algorithm design and the related calibration effort is becoming more and more challenging. Because of decreasing OBD thresholds, the monitoring strategy accuracy, which is tightly related with the components tolerances and the calibration quality, has to be improved. A model-based offline simulation of the monitoring strategies allows consideration of component and sensor tolerances as well as a first calibration optimization in the early development phase. AVL applied and improved a methodology that takes into account this information, which would require a big effort using testbed or vehicle measurements. In many cases a component influence analysis is possible before hardware is available for testbed measurements.

The rapidly growing complexity and the growing cross linking of powertrain components leads to longer development times, especially in the vehicle calibration process. The number of systems which need to be fitted to each other and the number of parameters to be calibrated in the particular systems are increasing tremendously. The extensive use of simulation promises to reduce the calibration effort by providing pre-optimized parameter sets. This paper describes a new simulation methodology by the interlinking of advanced vehicle simulation and evaluation tools, in particular the AVL-tools CRUISE, VSM and DRIVE. This methodology allows to semi automatically pre-optimize powertrain and vehicle parameters before hardware is involved. So far the pre-calibration of vehicle and powertrain parameters by simulation was not satisfying because of the missing of a reliable evaluation tool for the produced simulation results.

The de-icing process of the windscreen is a demanding problem in car climatization. In the first stages of the development procedure of air ducts, the numerical simulation plays an important role due to economy of time and money. Unfortunately, the available numerical methods for the generation of the computational grid and the simulation of the de-icing process are very time consuming and are complicated in handling. Therefore normally the quality of the de-icing process is evaluated with simplified simulation procedures or even with measurements late in the design process and necessary modifications are again time and cost consuming. The aim of this paper is to describe new methods for the de-icing simulation that will reduce meshing and calculation time by showing accurate results.

The AVL Load Matrix is a systematic approach to optimize durability and reliability test programs. It is based on component-specific test acceleration factors and uses damage models as well as statistics. Using the Load Matrix approach helps to achieve complete test programs while avoiding unrealistic over-testing. The paper describes the Load Matrix concept and structure as well as the process of setting up the Load Matrix for a system or component. Examples are provided on damage models, and the procedure to estimate the acceleration factors is discussed.

In order to improve the accuracy of vehicle simulation under transient cycle conditions and thus predict performance and fuel consumption, consideration of the complete system engine/drivetrain/vehicle is necessary. The coupling of otherwise independent simulation programs is therefore necessary for the vehicle and engine. The description of thermally transient processes enables the calculation of the heat balance of the engine, which in turn enables the simulation of warming up operation. Through consideration of the engine warming up process, the quality of the prediction of fuel consumption and emissions is improved. The combination of the simulation programs CRUISE and BOOST to determine the engine heat balance has proven to be successful for the analysis of transient drive cycles.

The well-to-wheel CO2 emissions and energy use of internal combustion engines (diesel and gasoline) are compared to fuel cell automotive propulsion systems. The fuel cell technologies investigated are polymer electrolyte fuel cell (PEFC), alkaline fuel cell (AFC) and solid oxide fuel cell (SOFC). The fuels are assumed to be produced from either crude oil or natural gas. The comparison is based on driving cycle simulations of a mid-class passenger car with an inertia test weight of 1350 kg. The study shows that the optimized diesel drive train (downsized mated to an integrated starter generator) achieves the best overall energy efficiency. The lowest CO2 emissions are produced by compressed natural gas (CNG) vehicles. Fuel cell propulsion systems achieve similar or even better CO2 emission values under hot start conditions but suffer from high energy input required during warm-up.