The resource-intensive process of road testing constitutes an essential part of the development of powertrain software. A significant proportion of explorative tests and adjustments for use in service are conducted during the vehicle test phase. However, the observed trends of decreasing development cycles and increasing system complexity generate a field of conflicts. In order to address this issue, this paper proposes road test emulation as a data-driven approach for continuously adapting powertrain software to the evolving overall system. A dedicated data strategy is designed to enhance customer-oriented software development. Therefore, test scenarios equivalent to in-service conditions are determined based on customer data. These test scenarios enable an emulation of road testing and the analysis of the system in a real-world operational context from the early stages of the product development process. System-specific data from the vehicle under development itself is utilised to define the initial parameter settings of the software. A generic approach to system-specific and customer-oriented calibration is presented. The example used is that of the causal, rule-based energy management of a performance-hybrid vehicle. This process results in the definition of an efficiency- and comfort-driven parameter set for the electric drive control, which is compared to a reference in various test scenarios. The method presented enables the data-driven generation of customer-oriented parameter sets and the quantification of the effects of comfort adjustments on the efficiency of the system in real-world operational contexts. Utilising software-in-the-loop simulations enables continuous implementation and iterative adjustments of the parameter sets and powertrain software throughout the product development process. The early consideration of in-service operations facilitates a shift-left in development activities. This supports an enhancement in the level of maturity at the beginning of road testing for the purposes of final calibration and testing of extreme conditions in the vehicle.
This publication analyzes the influence of cooling rate on the solid solution state during and after die casting of the AlSi9Cu3 alloy and, based on simulation and experimental results, predicts the R p0.2 yield strength as a function of cooling rate. The subject of the investigation is a four-cylinder in-line engine cast using the laminar die casting process. The implementation of a thermocouple in the casting mold enables in-situ measurement of the temperature-time behavior during the casting process, from filling the mold to demolding the component. Based on this measurement, the heat transfer coefficient between the casting mold and the melt is validated in the Magmasoft® casting simulation. The temperature-time behavior after demolding is reproduced using a specific test setup. The temperature measurements taken enable the existing casting simulation in Magmasoft® to be extended to the quenching process outside the casting mold. The correlation of the results of the tensile tests from the crankcase with the determined cooling rates enables the prediction of the R p0.2 yield strength as a function of the temperature-time behavior for the application of laminar die casting.
Die Digitalisierung und verkürzte Modellzyklen in der Automobilproduktion erfordern eine flexible und automatisierte Anpassung der Fertigungsprozesse. Dieser Beitrag stellt eine Referenzarchitektur für eine integrierte digitale Prozesskette vor, die den nahtlosen Informationsfluss von Fertigungsparametern aus der Fahrzeugentwicklung bis in die Produktion gewährleistet. Eine herstellerübergreifende Interoperabilität wird gleichermaßen berücksichtigt, wie die Einbindung aktueller und standardisierter Technologien. Die digitale Prozesskette umfasst Komponenten zur Datenerfassung, –verarbeitung sowie -kommunikation und wird im Rahmen des Projekts „Werk 4.0“ bei einem repräsentativen OEM der Automobilindustrie entwickelt.
In the Brazilian market, the 6x2 configuration for commercial vehicles is widely used. These vehicles feature a driven rear axle and a non-driven axle. For the non-driven axle, it is common to use a lifter system that allows the axle to be lifted when the vehicle is running empty. This system provides benefits such as reduced fuel consumption, lower tire wear, and reduced toll costs when charges are based on the number of axles in contact with the ground. Given these advantages, the system has a high demand, making it mandatory to perform a durability test prior to its market implementation. This paper will present the validation methodology for the lifter system bracket. To achieve this, the following stages will be discussed: CAE, instrumentation, data acquisition, test bench concept, test execution and results.
It is widely common for commercial vehicles to use Hotchkiss suspension with leaf springs attached to the solid axles. This configuration is cost effective and robust enough for the required application. The leaf springs evolved in the past decades in terms of new materials and construction, and the validation methods also changes. Since the application can be aggressive in some markets, physical tests are done to validate their durability and performance. Looking for a way to reduce development time and costs, high confidence level virtual validations are targeted by the whole industry. Using FEA fed by road load data as inputs for the loads applied to the leaf springs is an evolving methodology that can be considered as a high confidence level validation method, achieving very representative results, allowing engineering team to dismiss physical tests and release the item for production. The stages of spring development will be described in this paper, focusing on the virtual simulations and comparison to real data.
