The increasing emissions of greenhouse gases (GHG) and pollutants like particulate matter and nitrogen oxides (NOx) have led to environmental concerns. Hybrid and electric powertrains are being introduced as means to reduce pollutant emissions, especially at the local level. Additionally, the finite availability of fossil fuel sources, which are used to produce gasoline and diesel, highlights the need for alternative technical solutions. One approach to partly address these issues is lightweighting, which involves reducing the weight of vehicles to minimize their impact during the use phase. Mathematical models are employed to simulate the longitudinal dynamics of vehicles and estimate the energy required to accomplish driving missions. Appropriate metrics have been developed to quantify energy-saving effects that, in addition, can support the decision making, design, and development phase of future vehicles. To facilitate this process, it would be useful to build a database of ERV (Energy Reduction Value) and FRV (Fuel Reduction Value) figures derived through a unified procedure. Such a database would be useful in evaluating the effectiveness of vehicle lightweighting and its impact on energy consumption and pollutant emissions. The last phase of the analysis is the assessment of the overall reduction in the environmental impact of the vehicle throughout its life cycle by using the LCA (Life Cycle Assessment) approach. From this study, it was possible to conclude that lightweighting can be an appropriate solution to improve the energy efficiency of vehicles and that appropriate metrics, can support the development of new car models. The potential to integrate enhanced energy efficiency, lower emissions, and higher safety features into our everyday vehicles would represent a significant advancement in the automotive industry. There is a gap in the scientific literature on the effects of lightweighting on vehicle dynamics and energy usage which deserves to be investigated.

Nowadays, the topic of reducing vehicles’ energy consumption is very important. In particular, for electric vehicles, the reduction of energy consumption is necessary to remedy the most critical problems associated with this type of vehicle: the problem of the limited range of the electric traction, also associated with the long recharging times of the battery packs. To reduce use-phase impacts and energy consumptions of vehicles, it is useful to reduce the vehicle mass (lightweighting). The aim of this work is to analyze the parameters of a vehicle which influence the results of lightweighting, in order to provide guidelines for the creation of a vehicle model suitable for studying the effects of lightweighting. This study was carried out through two borderline case models, a compact car and an N1 vehicle, and simulating these through a consolidated vehicle simulation tool useful for consumption estimations. This study shows that the parameters that most influence the outcome of lightweighting are the rolling resistance, the battery pack characteristics, the aerodynamic coefficients, and the transmission efficiency, while the inertia contributions can be considered negligible. An analysis was also carried out with the variation of the driving cycle considered.

Today, reducing vehicle energy consumption is a crucial topic. For electric vehicles, reducing energy consumption is essential to address some of the most critical issues associated with this type of vehicle, such as the limited range of electric powertrains and the long battery recharging times. To lower the environmental impact during the vehicle’s use phase and reduce energy consumption, vehicle mass reduction (lightweighting) is an effective strategy. The objective of this work is to analyze the vehicle parameters that influence lightweighting outcomes on a real driving cycle, representative of the home-to-work travel in northern Italy. In particular, a previous work carried out on standard driving cycles is repeated in order to observe whether it is possible to draw the same conclusions regarding the variability in the lightweighting outcome. This study was conducted using two opposite vehicle models, a compact car and an N1 vehicle, simulated through a well-established vehicle simulation tool for energy consumption estimation. To conduct this analysis, several simulations with variable vehicle mass, and with different vehicle parameters, such as aerodynamics and rolling resistance, were performed to estimate energy consumption across a real-world driving cycle, acquired via GPS on board the vehicle during a home-to-work journey in northern Italy. This study reveals that even for the real driving cycle, as for the WLTC and US06 standards, the parameters that most influence the outcome of the lightening are the rolling resistance, the characteristics of the battery pack, the aerodynamic coefficients, and the efficiency of the transmission. Finally, the standard cycle that best fits with the real one considered in this study is the Artemis Urban Cycle.

The so-called porpoising is a well-known problem similar to bouncing that is affecting the dynamic behavior of basically all the field of 2022 Formula 1 racing cars. It is due to the extreme sensitivity of aerodynamic loads to ride height variations along a lap. Mid-way through the season race engineers are still struggling to cope with this phenomenon and its consequences, with regard to either physiological stress experienced by the drivers or to overall vehicle performance and stability. The paper introduces two kinds of models based on real-world chassis and aerodynamic data, where the above-mentioned downforce sensitivity has been arbitrarily recreated through the application of a decay function to aero maps. The first one is a quasi-static model, usually adopted as a trackside tool for controlling ride heights and aero balance, while the second, a fully dynamic model, recreates the interaction between oscillating aerodynamic loads and suspension dynamics resulting in a visible porpoising phenomenon. Basic setup changes have been tested, including significant static ride height variations. The paper should be seen as a proposal of guidelines in the search of a trade-off between aerodynamic stability and overall performance, without pretention of quantitative accuracy due to the highly confidential topic, which makes numerical validation impossible.

Today, reducing vehicle energy consumption is a crucial topic. For electric vehicles, reducing energy consumption is essential to address some of the most critical issues associated with this type of vehicle, such as the limited range of electric powertrains and the long battery recharging times. To lower the environmental impact during the vehicle’s use phase and reduce energy consumption, vehicle mass reduction (lightweighting) is an effective strategy. The objective of this work is to analyze the vehicle parameters that influence lightweighting outcomes on a real driving cycle, representative of the home-to-work travel in the northern Italy. In particular, a previous work carried out on standard driving cycles is repeated, in order to observe whether it is possible to draw the same conclusions regarding the variability of the lightweighting outcome. This study was conducted using two opposite vehicle models, a compact car and an N1 vehicle, simulated through a well-established vehicle simulation tool for energy consumption estimation. The study reveals that even for the real driving cycle, as for the WLTC and US06 standards, the parameters that most influence the outcome of the lightening are rolling resistance, the characteristics of the battery pack, the aerodynamic coefficients and the efficiency of the transmission. Finally, the standard cycle that best fits with the real one considered in this study is the Artemis Urban Cycle.

Suspension and steering design play a major role in ensuring the correct dynamic behavior of road vehicles. Passenger cars are especially demanding from this point of view: NVH and ride comfort requirements often collide with active safety-related requirements such as road holding in steady-state conditions and stability in transients. Driving pleasure is also important for market success, therefore accurate steering feedback and predictable handling properties are additional priorities. Since flexible bushings are used as interface between the suspension arms and the chassis, extra degrees-of-freedom make the design process a complex task. While the use of a multibody software is common practice in the industry, a dedicated computational tool can be more practical and straightforward, especially when undertaking the design of a new suspension concept ground-up. The paper presents a computational methodology for the design of an independent suspension with the associated kinematic and compliance attributes. Typical elastokinematic properties like toe, camber, wheelbase, and track variations versus tyre forces and moments can be computed by means of a dedicated software tool. A sort of validation was performed either by means of a comparison with a MathWorks Simscape® Multibody based model. Finally, a sensitivity analysis is given as an example. Computationally, the method proposed is intuitively based on the equilibrium equations. The nonlinear equations are then solved with Newton–Raphson algorithm. The method can be also optimized for computational efficiency and is thoroughly described so that the reader can easily replicate it in the desired programing environment.