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Due to the recent anti-pollution policies, the performance increase in Spark Ignition (SI) engines is currently under the focus of automotive manufacturers. This trend drives control systems designers to investigate accurate solutions and build more sophisticated algorithms to increase the efficiency of this kind of engines. The development of a control strategy is composed of several phases and steps, and the first part of such process is typically spent in defining and investigating the logic of the strategy. During this phase it is often useful to have a light engine simulator, which allows to have robust synthetic combustion data with a low calibration and computational effort. In the first part of this paper, a description of the control-oriented ANalytical Engine SIMulator (ANESIM) is carried out.

During the development of an Internal Combustion Engine-based powertrain, traditional procedures for control strategies calibration and validation produce huge amount of data, that can be used to develop innovative data-driven applications, such as emission virtual sensing. One of the main criticalities is related to the data quality, that cannot be easily assessed for such a big amount of data. This work focuses on an emission modeling activity, using an enhanced Light Gradient Boosting Regressor and a dedicated data pre-processing pipeline to improve data quality. First thing, a software tool is developed to access a database containing data coming from emissions tests. The tool performs a data cleaning procedure to exclude corrupted data or invalid parts of the test. Moreover, it automatically tunes model hyperparameters, it chooses the best set of features, and it validates the procedure by comparing the estimation and the experimental measurement.

This article, deriving from the author's PhD research activity [1], contains an in-depth analysis of the stresses exerted on the crankcase of a Ducati 999 by its engine. The machine design study was financed by Ducati Motor Holding and involved several doctoral theses [2-3]. It ventures into a relatively unexplored field: the results achieved are set to become strategically important due to the size of the motorcycle market and to the strong appeal of motorcycle racing.

Powertrain controller design is among the most challenging problems due to the complexity of the functions that the system has to support, to the safety aspects and to the cost limits imposed by car manufacturers. To compound these difficulties, time-to-market requirements are becoming more and more stringent. Design time, continuously changing specifications and safety considerations have pushed the design more and more towards software implementation of the main functionality. Software has been traditionally designed with very little abstraction in mind thus forcing a tight dependency of the implementation on the particular hardware architecture, e.g., the instruction set of the micro- controller. Software legacy has made the rapid adoption of new technology and IC's almost impossible, stifling innovation. In addition, the absence of a correct abstraction hierarchy made verifying the correctness of the behavior of the system as well as adding new functionality extremely difficult.

A unique differential assembly was needed for the Lawrence Technological University (LTU) SAE Formula race car. Specifically, a differential was required that had torque sensing capabilities, perfect reliability, high strength, light weight, the ability to withstand inertia and shock loading, a small package, no leaks, the ability to support numerous components. In that regard, an existing differential was selected that had the torque sensing capabilities, but had deficiencies that needed to be fixed. Those deficiencies included the following: Differential unit was over 4 kg unmounted, with no housing. This was considered too heavy, when housed properly. Bearing surface was provided on only one end of the carrier. This design provides insufficient bearing surface to support either the differential housing or half-shafts The internal drive splines integral to the case are not optimized for a perpendicular drive/axle arrangement, such as, a chain drive.

New gasoline engine design is highly influenced by CO2 and emission limits defined by legislations, the demand for real conditions fuel economy, higher torque, higher specific power and lower cost. To reach the requirements coming from the end-users and legislations, especially for SI engines, several technologies are available, such as downsizing, including turbocharging in combination with direct injection. These technologies allow to solve the main issues of gasoline engines in terms of efficiency and performance which are knocking, part-load losses, and thermal stress at high power conditions. Moreover, other possibilities are under evaluation to allow further steps of enhancement for the even more challenging requirements. However, the benefits and costs given by the mix of these technologies must be accurately evaluated by means of objective tools and procedures in order to choose among the best alternatives.

This paper presents a 14 degrees of freedom vehicle model. Despite numerous software are nowadays commercially available, the model presented in this paper has been built starting from a blank sheet because the goal of the authors was to realize a model suitable for real-time simulation, compatible with the computational power of typical electronic control units, for on-board applications. In order to achieve this objective a complete vehicle dynamics simulation model has been developed in Matlab/Simulink environment: having a complete knowledge of the model's structure, it is possible to adapt its complexity to the computational power of the hardware used to run the simulation, a crucial feature to achieve real-time execution in actual ECUs.