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On the path to decarbonizing road transport, electric commercial vehicles will play a significant role. The first applications were directed to the smaller trucks for distribution traffic with relatively moderate driving and range requirements, but meanwhile, the first generation of a complete portfolio of truck sizes is developed and available on the market. In these early applications, many compromises were accepted to overcome component availability, but meanwhile, the supply chain can address the specific needs of electric trucks. With that, the optimization towards higher usability and lower costs can be moved to the next level. Especially for long-haul trucks, efficiency is a driving factor for the total costs of ownership. Besides the propulsion system, all other systems must be optimized for higher efficiency. This includes thermal management since the thermal management components consume energy and have a direct impact on the driving range.

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.

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.

With the implementation of EURO VI and similar emission legislation, the industry assumed the pace and stringency of new legislation would be reduced in the future. The latest announcements of proposed and implemented legislation steps show that future legislation will be even more stringent. The currently leading announced legislation, which concerns a large number of global manufacturers, is the legislation from the United States (US) Environmental Protection Agency (EPA) and the California Air Resources Board (CARB). Both announced new legislation for CO2, Greenhouse Gas (GHG) Phase II. CARB is also planning additional Ultra Low NOx regulations. Both regulations are significant and will require a number of technologies to be used in order to achieve the challenging limits. AVL published some engine related measures to address these legislation steps.

No abstract available.

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.

One main general goal during product development in the passenger car industry as well as in the commercial vehicle industry is to reduce time to market. The customer wants to get the newest product and is not accepting the risk of any product call backs. This means the minimization of the risk of field claims for the manufacturer. The challenge to reach this goal is a capable volume production of each new product. To create a competitive, innovative product it is the task for design and simulation engineers in the development phase to design the product in view of function, efficiency, fatigue strength, optimized weight and optimized product costs. Additionally an agreement between design and industrial production planning is required. An early involvement of production engineers into the development of a product ensures design for manufacturing from the very beginning.

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.

Worldwide OBD legislation has and will be tightened drastically. In the US, OBD II for PC and the introduction of HD OBD for HD vehicles in 2010 will be the next steps. Further challenges have come up with the introduction of active exhaust gas aftertreatment components to meet the lower future emission standards, especially with the implementation of combined DPF-De-NOx-systems for PC and HD engines. Following such an increase in complexity, more comprehensive algorithms and software have to be developed to cope with the legislative requirements for exhaust gas aftertreatment devices. The calibration has to assure the proper functionality of OBD under all driving situations and ambient conditions. The increased complexity can only be mastered when new and efficient tools and methodologies are applied for both algorithm design and calibration. Consequently, OBD requirements have to be taken into account right from the start of engine development.

The reduction of nitrous oxides in the exhaust gases of internal combustion engines using a urea water solution is gaining more and more importance. While maintaining the future exhaust gas emission regulations, like the Euro 6 for passenger cars and the Euro 5 for commercial vehicles, urea dosing allows the engine management to be modified to improve fuel economy as well. The system manufacturer Robert Bosch has started early to develop the necessary dosing systems for the urea water solution. More than 300.000 Units have been delivered in 2007 for heavy duty applications. Typical dosing quantities for those systems are in the range of 0.01 l/h for passenger car systems and up to 10 l/h for commercial vehicles. During the first years of development and application of urea dosing systems, instantaneous flow measuring devices were used, which were not operating fully satisfactory.

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.

Fuel Cells (FC) are promising candidates to reduce energy consumption and, hence, to improve the global climate situation due to significant gains in the process efficiencies. Whereas the development of fuel cells for passenger car applications has intensified during the last years, commercial vehicle applications have not been in the focus of developers so far. A reason for that is the limited availability of fuels such as hydrogen. Commercial vehicles are in the most cases operated with diesel fuel. AVL has developed three fuel cell applications for commercial vehicles operated with diesel fuel.

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.