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The clutch is that mechanical part located in an internal combustion engine vehicle which allows the torque transmission from the shaft to the wheels, permitting at the same time gear shifting and supporting engine revolutions while the car is idling. This component exploits friction as working principle, therefore heat generation is in its own nature. The comprehension of all the critical issues related to thermal emission, and also of the principal physical parameters driving the phenomena are a must in design phases. The subject of this paper is the elaboration of an accurate, but also easy to use and easily replicable, methodology to simulate thermal behavior of a clutch operating inside its usual environment. The present methodology allows to prevent corrective actions in the last phase of the projects (real testing), such as changes in gear ratios, that likely worsen CO2 emissions, permitting to achieve the wished thermal performance of the clutch avoiding late changes.

A method for estimating the vehicle mass in real time is presented. Traditional mass estimation methods suffer due a lack of knowledge of the vehicle parameters, the road surface conditions and most importantly the effect of the vehicle transmission. To resolve these issues, a method independent of a vehicle model is utilized in conjunction with a drivetrain output torque observer to obtain the estimate of the vehicle mass. Simulations and experimental track tests indicate that the method is able to accurately estimate the vehicle mass with a relatively fast rate of convergence compared to traditional methods.

The term driveability describes the driver's complex subjective perception of the interactions with the vehicle. One of them is associated to longitudinal acceleration aspects. A relevant contribution to the driveability optimization process is, nowadays, realized by means of track tests during which a considerable amount of driveline parameters are tuned in order to obtain a good compromise of longitudinal acceleration response. Unfortunately, this process is carried out at a development stage when a design iteration becomes too expensive. In addition, the actual trend of downsizing and supercharging the engines leads to higher vibrations that are transmitted to the vehicle. A large effort is therefore dedicated to develop, test and implement ignition strategies addressed to minimize the torque irregularities. Such strategies could penalize the engine maximum performance, efficiency and emissions. The introduction of the dual mass flywheel is beneficial to this end.

In this paper a test bench for measuring the Static Transmission Error of two mating gears is presented and a comparison with the results obtained with the commercial software GeDy TrAss is shown. Static Transmission Error is considered as the main source of overloads and Noise, Vibration and Harshness issues in mechanical transmissions. It is defined as the difference between the theoretical angular position of two gears under load in quasi-static conditions and the real one. This parameter strictly depends on the applied torque and the tooth macro and micro-geometry. The test bench illustrated in this work is designed to evaluate the actual Static Transmission Error of two gears under load in quasi-static conditions. In particular, this testbed can be divided in two macro elements: the first one is the mechanism composed by weights and pulleys that generates a driving and a braking torque up to 500 Nm.

This paper presents a methodology for the assessment of the NVH (noise vibration and harshness) performance of Dual Clutch Transmissions (DCTs) depending on some transmission design parameters, e.g. torsional backlash in the synchronizers or clutch disc moment of inertia, during low speed maneuvers. A 21-DOFs nonlinear dynamic model of a C-segment passenger car equipped with a DCT is used to simulate the torsional behavior of the driveline and to estimate the forces at the bearings. The impacts between the teeth of two engaging components, e.g. gears and synchronizers, generate impulses in the forces, thus loading the bearings with force time-history characterized by rich frequency content. A broadband excitation is therefore applied to the gearbox case, generating noise and vibration issues.

The current electrification trend involving hybrid and electric vehicles requires accurate tools to evaluate performance and reliability of electric powertrains’ control systems. Thanks to Hardware in the Loop (HiL) technique, verification, validation and virtual calibration of Electronic Control Systems can be performed without physical plants, addressing the need of frontloading, cost and time reduction of new vehicles control systems development. However, HiL applications with power electronics controllers brings several concerns due to the extremely low timestep needed for accurate simulation of electromagnetic phenomena, making FPGA-based simulation the only option. Moreover, thermal aspects of electric motors are very important from the control perspective as complex thermal management control strategies are implemented to improve the efficiency and to prevent overheating that can cause permanent damage to the electrical machine.

Magneto-Rheological (MR) Fluid started to be used for industrial applications in the last 20 years, and, from that moment on, innovative uses have been evaluated for different applications to exploit its characteristic of changing yield stress as a function of the magnetic field applied. Because of the complexity of the behavior of the MR fluid, it is necessary to perform lots of simulations, combining multi-physical software capable of evaluating all the material’s characteristics. The paper proposes a strategy capable of quickly verifying the feasibility of an innovative MR system, considering a sufficient accuracy of the approximation, able to easily verify the principal criticalities of the innovative applications concerning the MR fluid main electromagnetic and fluid-dynamic capabilities.

Range anxiety in current battery electric vehicles is a challenging problem, especially for commercial vehicles with heavy payloads. Therefore, the development of electrified propulsion systems with multiple power sources, such as fuel cells, is an active area of research. Optimal speed planning and energy management, referred to as eco-driving, can substantially reduce the energy consumption of commercial vehicles, regardless of the powertrain architecture. Eco-driving controllers can leverage look-ahead route information such as road grade, speed limits, and signalized intersections to perform velocity profile smoothing, resulting in reduced energy consumption. This study presents a comprehensive analysis of the performance of an eco-driving controller for fuel cell electric trucks in a real-world scenario, considering a route from a distribution center to the associated supermarket.

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.

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.

Electric vehicles comprising multiple motors allow the individual wheel torque allocation, i.e. torque-vectoring. Powertrain configurations with multiple motors provide additional degree of freedom to improve system level efficiencies while ensuring handling performances and active safety. However, most of the works available on this topic do not simultaneously optimize both vehicle dynamic performance and energy efficiency while considering the real-time implementability of the controller. In this work, a new and systematic approach in designing, modeling, and simulating the main layers of a torque-vectoring control framework is introduced. The high level control combines the actions of an adaptive Linear Quadratic Regulator (A-LQR) and of a feedforward controller, to shape the steady-state and transient vehicle response by generating the reference yaw moment. A novel energy efficient torque allocation method is proposed as a low level controller.

With electric vehicles becoming more and more popular, the classic “general purpose” vehicle concept is changing to a “dedicated vehicle” concept. Light trucks for goods delivery in cities are one of the examples. The European vehicle category L7e fits perfectly in the low power, low weight vehicle requirements for an electric light truck for goods delivery. However, the safety requirements of this vehicle category are very low and their occupants are highly exposed to injuries in the event of a collision. The European Commission co-funded project OPTIBODY (Optimized Structural components and add-ons to improve passive safety in new Electric Light Trucks and Vans) is developing a new structural concept based on a chassis, a cabin a several add-ons. The add-ons will provide improved protection in case of frontal, side and rear impact.

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.

When developing a new engine control strategy, some of the important issues are cost, resource minimization, and quality improvement. This paper outlines how a model based approach was used to develop an engine control strategy for an Extended Range Electric Vehicle (EREV). The outlined approach allowed the development team to minimize the required number of experiments and to complete much of the control development and calibration before implementing the control strategy in the vehicle. It will be shown how models of different fidelity, from map-based models, to mean value models, to 1-D gas dynamics models were generated and used to develop the engine control system. The application of real time capable models for Hardware-in-the-Loop testing will also be shown.

The production of multi-mode power-split hybrid vehicles has been implemented for some years now and it is expected to continually grow over the next decade. Control strategy still represents one of the most challenging aspects in the design of these vehicles. Finding an effective strategy to obtain the optimal solution with light computational cost is not trivial. In previous publications, a Power-weighted Efficiency Analysis for Rapid Sizing (PEARS) algorithm was found to be a very promising solution. The issue with implementing a PEARS technique is that it generates an unrealistic mode-shifting schedule. In this paper, the problematic points of PEARS algorithm are detected and analyzed, then a solution to minimize mode-shifting events is proposed. The improved PEARS algorithm is integrated in a design methodology that can generate and test several candidate powertrains in a short period of time.

As technology evolves, the number of sensors and available data on vehicles grow exponentially. In this context, it is essential to use sensors for monitoring key components, increasing safety and reliability, and gathering data useful for mechanical dimensioning and control systems. This paper presents an application of strain-gauged bolts on brake calipers fixation of two electric vehicles. With this approach it was possible to evaluate the loads applied to the brake pads fixation zone and correlate them with braking behavior, therefore gaining insights on braking conditions and system state for an improved braking function control. The goal of the study is analyzing the strengths and limitations of the method and proposing developments to deploy it in real applications. This is particularly important and novel for electric vehicles, where powertrains can create positive/negative torques and generate complex interactions with braking system.

This paper deals with the energy efficiency of cooperative cruise control technologies when considering vehicle strings in a realistic driving environment. In particular, we design a cooperative longitudinal controller using a state-of-the-art model predictive control (MPC) implementation. Rather than testing our controller on a limited set of short maneuvers, we thoroughly assess its performance on a number of regulatory drive cycles and on a set of driving missions of similar length that were constructed based on real driving data. This allows us to focus our assessment on the energetic aspects in addition to testing the controller’s robustness. The analyzed controller, based on linear MPC, uses vehicle sensor data and information transmitted by the vehicle driving the string to adjust the longitudinal trajectory of the host vehicle to maintain a reduced inter-vehicular distance while simultaneously optimizing energy efficiency.

In the last years, the design in the automotive sector is mainly led by emission reduction and circular economy. To satisfy the first perspective, composites materials are being increasingly used to produce lightweight structural and semi-structural components. However, the automotive mass production arises the problem of the end-of-life disposal of the vehicle and the reduction of the wastes environmental impact. The circular economy of the composite materials has therefore become a challenge of primary importance for car manufacturers and tier 1 suppliers. It is necessary to pursue a different economic model, combining traditional raw materials with the intensive use of materials from recycling processes. New technologies are being studied and developed concerning the reuse of in-line production scraps with out-of-autoclave process that makes them desirable for high production rate applications.

This paper presents the analysis of an innovative braking system as an alternative and environmentally friendly solution to traditional automotive friction brakes. The idea arose from the need to eliminate emissions from the braking system of an electric vehicle: traditional brakes, in fact, produce dust emissions due to the wear of the pads. The innovative solution, called Zero-Emissions Driving System (ZEDS), is a system composed of an electric motor (in-wheel motor) and an innovative brake. The latter has a geometry such that it houses MagnetoRheological Fluid (MRF) inside it, which can change its viscous properties according to the magnetic field passing through it. It is thus an electro-actuated brake, capable of generating a magnetic field passing through the fluid and developing braking torque. A performance analysis obtained by a simulation model built on Matlab Simulink is proposed.

Gearbox behavior is strictly affected by gears, shaft, bearings and casing stiffnesses. As a matter of fact, their contribution to gear dynamics is fundamental for mechanical transmissions design. In this paper a semi-analytical model developed for the estimation of the dynamic behavior of two mating gears is presented and tested on two case studies. Starting with the estimation of the Static Transmission Error, intended as the difference between the theoretical and actual angular position between the two mating gears, the dynamic behavior of the mating elements is estimated by means of a Dynamic Model. The Dynamic Model takes into account the gears, the contact between teeth exchanging loads and the other mechanical elements reduced by means of a DOF reduction technique. Based on the block-oriented approach, Dynamic Model allows the user to easily manage the complexity of the system with further or less elements by adding or removing DOFs.