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The paper deals with the design and manufacturing of a McPherson suspension arm made from short glass fiber reinforced polyamide (PA66). The design of the arm and the design of the molds have been made jointly. According to Industry 4.0 paradigms, a full digitalization of both the product and process has been performed. Since the mechanical behavior of the suspension arm strongly depends on constraints which are difficult to be modelled, a simpler structure with well-defined mechanical constraints has been developed. By means of such simple structure, the model for the behavior of the material has been validated. Since the suspension arm is a hybrid structure, the associated simple structure is hybrid as well, featuring a metal sheet with over-molded polymer. The issues referring to material flow, material to material contact, weld lines, fatigue strength, high and low temperature behavior, creep, dynamic strength have been investigated on the simple structure.

Sustainable and energy-efficient consumption is a main concern in contemporary society. Driven by more stringent international requirements, automobile manufacturers have shifted the focus of development into new technologies such as Hybrid Electric Vehicles (HEVs). These powertrains offer significant improvements in the efficiency of the propulsion system compared to conventional vehicles, but they also lead to higher complexities in the design process and in the control strategy. In order to obtain an optimum powertrain configuration, each component has to be laid out considering the best powertrain efficiency. With such a perspective, a simulation study was performed for the purpose of minimizing well-to-wheel CO2 emissions of a city car through electrification. Three different innovative systems, a Series Hybrid Electric Vehicle (SHEV), a Mixed Hybrid Electric Vehicle (MHEV) and a Battery Electric Vehicle (BEV) were compared to a conventional one.

This paper presents a technique for extracting modal parameters of a linear multi degree of freedom system in the frequency domain. The roots of the technique are the well known rational fraction polynomials method but emphasis is given to the application to output-only data in the form of cross-spectral density functions. A discussion is presented on the possibility of achieving reliable results also for structures undergoing multiple input excitations. Numerical stability of the technique is obtained by properly scaling both the frequency and the cross-spectrum axes. Good performance of the method are shown for numerical examples and for a test case on an actual structure.

Over the last decades, the use of computers has become an integral part of the engine development process. Computer-based tools are increasingly used in the design process, and especially the layout of the various subsystems is conducted by means of simulation models. Computer-aided engineering plays a central role e.g. in the design of the combustion process as well as with regards to work performed in the area of engine mechanics, where CFD, FEM, and MBS are applied. As a parallel trend, it can be observed that various engine performance characteristics such as e.g. the specific power output and the power-to-weight ratio have undergone an enormous increase, a trend which to some extent counteracts the increase in safety against malfunction and failure. As yet, due to the constant need for further optimization, mechanical testing and verification processes have not become redundant, and it is assumed that they will remain indispensable for the foreseeable future.

Experimental Design methodologies have been applied in conjunction with objective functions for the optimization of the internal geometry of a rear muffler of a subcompact car equipped with a 1.4 liters displacement s.i. turbocharged engine. The muffler also features an innovative variable geometry design. The definition of an objective function summarising the silencing capability of the muffler has been driving the optimization process with the aim to reduce the tailpipe noise while maintaining acceptable pressure losses and complying with severe space constraints. Design of Experiments techniques for the reduction of experimental plans have been shown to be extremely effective to find out the optimum values of the design parameters, allowing a remarkable reduction of the time required by the design process in comparison with full factorial designs.

During the past years, there has been an increasing tendency to seriously question and break up old and ingrained structures in combustion engine testing. The reason for this is the continuously increasing number of engine and vehicle variants and a variety of applications resulting from it, which significantly push up development costs and times when carrying out the classical testing patterns. The following article by FEV Motorentechnik GmbH introduces a comprehensive test methodology for purposeful endurance testing of modern drive units (in particular from the fields of passenger cars and commercial vehicles). The procedure and the testing philosophy are explained in detail, illustrated by a concrete development example.

Calculating the bearing reliability and behavior is one of the primary tasks which have to be performed to define the main dimensions of the cranktrain of an internal combustion engine. Since the bearing results are essential for the pre-layout of the cranktrain, the conclusion on the bearing safety should be met as early as possible. Therefore detailed simulations like T-EHD or EHD analysis may not be applied to define the dimensions in such an early development phase. In the frame of this study a prediction methodology, based on a HD bearing approach, for bearing reliability of inline-4 crankshafts of passenger cars is proposed. In this way not only the design phase is shortened but also achieving the optimal solution is simplified. Moreover the requirement of a CAD model is eliminated for the preliminary design phase. The influencing parameters on the bearing behavior are first selected and divided into two groups: geometry and loading.

The new Thermo-Elasto-Hydro-Dynamic (TEHD) code developed by FEV, is designed to improve the predictability of journal bearing designs and thereby increase the reliability of safety factors in the development of highly loaded internal combustion engines. Advanced analysis tools are evaluated by their performance as well as by their ease of use. High performance means on the one hand: taking into account all the important characteristics, like bearing elasticity or cavitation effects, to mention only some major parameters for modern journal bearing analysis. On the other hand: an economic run-time behavior must be a key feature concerning usability of the TEHD-demands for daily development praxis. Ease of use means also, that the TEHD model can easily be used as a plug-in routine of an already existing software package that is well known to the development departments.

The requirements for diesel and gasoline engines are continuously increasing with respect to emissions, fuel consumption and durability. Besides the engine development process the quality of the production engine itself has to be ensured. This paper discusses alternative philosophies and approaches in terms of the quality management process. Based on a detailed analysis of the required equipment advanced solutions are presented. Modular containerized test cells are described being equipped exactly to the current testing task ready to use in low infrastructure. The testing capacity of the facility can be adjusted to the actual production volume by simply removing or adding modular test cells. Thus, at every facility the testing tasks can be executed successfully and the investment can be kept low.

In the present paper, starting from a first attempt design of engine components, a CAD/CAE integrated approach for designing engine is proposed. As first step, some typological quantities are setting in order to define the designed engine, for example the number of cylinders, displacements, thermodynamic cycle and geometrical constraints. Using literature approach and tailored design methodologies, the developed software provides the geometric parameters of the main engine components: crankshaft, piston, wrist pin, connecting rod, bedplate, engine block, cylinder head, bearings, valvetrain. Form the geometrical parameters, the developed software, using 3D CAD parametric models, defines a first functional model of each component and of their mutual interactions. Then a numerical analysis can be evaluated and it provides important feedback result for design targets. In the paper the particular case of a crank mechanism model is presented.

A fuel-cell-based system's performance is mainly identified in the overall efficiency, strongly depending on the amount of power losses due to auxiliary devices to supply. In such a situation, everything that causes either a decrease of the available power output or an increment of auxiliary losses would determine a sensible overall efficiency reduction.

Modern powertrain development is targeting to meet challenging, to some degrees contradictory development goals in a short timeframe. Looking to a development time schedule of 36 months from concept to SOP, it becomes a prerequisite that unnecessary design loops have to be avoided by all means. Now, in addition, the experimental development work has to be conducted more efficiently than in the past. In recent years methods for an efficient design process have been successfully applied. Testing and vehicle application work can take advantage of methods empowered by model based approaches. Today, models with different levels of detail are able to significantly improve nearly every development phase. Supported by standardized and automated test bench and vehicle procedures an efficient and comprehensive development process can be established and utilized, which is also necessary to tackle growing complexity.

Nowadays internal combustion engine design is characterized by a faster development time with increased levels of quality, NVH, specific power and lower weight all being demanded at a lower production cost. This requires a new and systemic design management from the outset of the concept to SOP (Start of Production). The design for Six Sigma (DFSS) process is the surest way to achieve the above mentioned development goals. Within a Six Sigma approach, manufacturing and serial production issues are considered from the beginning of the development phase. Based on examples, the methodology will be explained in single steps. The explanation will include QFD, FMEA (product and process), scorecards, DOE and kneading process with its tolerance analysis and process capability investigations. The use of these different tools for each phase of the design process will be described.

Predicting the fuel economy capability of hybrid electric vehicle (HEV) powertrains by solving the related optimal control problem has been available for a few decades. Dynamic programming (DP) is one of the most popular techniques implemented to this end. Current research aims at integrating further powertrain modeling criteria that improve the fidelity level of the optimal HEV powertrain control behavior predicted by DP, thus corroborating the reliability of the fuel economy assessment. Dedicated methodologies need further development to avoid the curse of dimensionality which is typically associated to DP when increasing the number of control and state variables considered. This paper aims at considerably reducing the overall computational effort required by DP for HEVs by removing the state term associated to the battery state-of-charge (SOC).

Climate change has become a real problem in our world. Society is trying to contain it as much as possible, promoting more sustainable behaviors and limiting pollution. For the automotive industry, this leads to progressive electrification and reduction of tailpipe emissions and fuel consumption for conventional vehicles. In this framework, this paper presents the design of a vehicle to compete in the Urban Concept category of Shell Eco Marathon, a competition among universities that has the goal to release a vehicle with the lowest possible fuel consumption. This work describes the monocoque design phases of the vehicle JUNO. The complete design approach is described, through the analysis of the decisional workflow adopted to integrate every technical solution from the aerodynamic constraints to the structural ones passing from the vehicle dynamic requirements.

Designing automobile brake systems is generally complex and time consuming. Indeed, the brake system integrates several components and has to satisfy numerous conflicting government regulations. Due to these constraints, designing an optimal configuration is not easy. This paper consequently proposes a simple, intuitive and automated methodology that enables rapid optimal design of light vehicle hydraulic brake systems. Firstly, the system is modeled through cascaded analytical equations for each component. A large design space is then generated by varying the operational parameters of each component in its specific reasonable range. The system components under consideration include the brake pedal, the master cylinder, the vacuum-assisted booster, the brake line and the brake pistons. Successful system configurations are identified by implementing the requirements of the two most relevant safety homologation standards for light vehicle brake systems (US and EU legislations).

The complexity of automotive market, the request of new gearbox layout able to improve the efficiency of a vehicle and the requirement of quick and effective design of gearboxes push the designers to seek new technologies, new layouts, new solutions. The typical development of a gearbox requires a lot of time and engineers' effort and it often implies a lot of time to define the right layout. The idea of developing a "paradigm" able to guide the designer through the design process seems to be effective. Starting from the experience of a code called "Engine Paradigm" where such idea was firstly implemented, the authors propose in the present paper the development of a code able to suggest a first attempt design of a gearbox. The "Gearbox Paradigm" code requires few data introduction, as torque, power, number of gears, some geometrical constraints such as the axes gap the gearbox layout, and the code elaborates a proposal of CAD design of a gearbox.

Hybrid electric vehicles (HEVs) represent a fundamental step in the global evolution towards transportation electrification. Nevertheless, they exhibit a remarkably complex design environment with respect to both traditional internal combustion engine vehicles and battery electric vehicles. Innovative and advanced design tools are therefore crucially required to effectively handle the increased complexity of HEV development processes. This paper aims at providing a comprehensive overview of past and current advancements in HEV powertrain design methodologies. Subsequently, major simplifications and limits of current HEV design methodologies are detailed. The final part of this paper defines research challenges that need accomplishment to develop the next generation HEV architecture design tools.

This paper presents a complete overview of the computational design of an advanced suspension control arm constructed of composite material for light weighting purposes. The proposed methodology presented in detail is split into 3 phases. Phase 1 or Vehicle Performance Simulation, in which basic modelling and a sensibility study is performed to better understand the advantages of unsprung mass reduction (compared to sprung mass reduction) with respect to the vehicle’s vertical dynamics. It followed by the development and utilization of a multibody approach to evaluate the full-vehicle response to different dynamic maneuvers, such as harsh road imperfections, sine sweep steering, and double lane change tests. The impact of the improved suspension control arm is highlighted in detail, and the loads to which it is subjected are computed to serve as inputs for the successive phases.

Traditional CACC systems utilize inter-vehicle wireless communication to maintain minimal yet safe inter-vehicle distances, thereby improving traffic efficiency. However, introducing communication delays generates system uncertainties that jeopardize string stability, a crucial requirement for robust CACC performance. To address these issues, we introduce a decentralized Model Predictive Control (MPC) approach that incorporates Kalman Filters and state predictors to counteract the uncertainties posed by noise and communication delays. We validate our approach through MATLAB Simulink simulations, using stochastic and mathematical models to capture vehicular dynamics, Wi-Fi communication errors, and sensor noises. In addition, we explore the application of a Reinforcement Learning (RL)-based algorithm to compare its merits and limitations against our decentralized MPC controller, considering factors like feasibility and reliability.