Search Results

Monitoring and preserving state-of-health of high-voltage battery packs in electrified road vehicles currently represents an open and growing research topic. When predicting high-voltage battery lifetime, most current literature assumes a uniform temperature distribution among the different cells of the pack. Nevertheless, temperature has been demonstrated having a key impact on cell lifetime, and different cells of the same battery pack typically exhibit different temperature profiles over time, e.g. due to their position within the pack. Following these considerations, this paper aims at assessing the effect of temperature distribution on the predicted lifetime of cells belonging to the same battery pack. To this end, a throughput-based numerical cell ageing model is firstly selected due to its reasonable compromise between accuracy and computational efficiency.

In the last few years, the number of Advanced Driver Assistance Systems (ADAS) on road vehicles has been increased with the aim of dramatically reducing road accidents. Therefore, the OEMs need to integrate and test these systems, to comply with the safety regulations. To lower the development cost, instead of experimental testing, many virtual simulation scenarios need to be tested for ADAS validation. The classic multibody vehicle approach, normally used to design and optimize vehicle dynamics performance, is not always suitable to cope with these new tasks; therefore, real-time lumped-parameter vehicle models implementation becomes more and more necessary. This paper aims at providing a methodology to convert experimentally validated light commercial vehicles (LCV) multibody models (MBM) into real-time lumped-parameter models (RTM).

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.

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.

Vehicle dynamics estimation has been the subject of study for some years now. If on-board vehicle control systems can be provided with information such as side slip angle, lateral force etc. then stability of the vehicle can be improved. To estimate these dynamic variables different observers have been used e.g., sliding mode, fuzzy logic, neural networks etc. In this article the authors propose an extended Kalman filter to estimate vehicle side slip angle. Roll angle is estimated using vertical loads as input. First, a linear Kalman filter is used to filter out the vertical forces and estimate roll angle. This information is then used to estimate the vehicle side slip angle. To take into account the nonlinearities concerning lateral vehicle dynamics, Pacejka magic formula is used to model lateral forces. Estimated results are then compared with simulations, showing good accuracy.

Modern vehicles have several active systems on board such as the Electronic Stability Control. Many of these systems require knowledge of vehicle states such as sideslip angle and yaw rate for feedback control. Sideslip angle cannot be measured with the standard sensors present in a vehicle, but it can be measured by very expensive and large optical sensors. As a result, state observers have been used to estimate sideslip angle of vehicles. The current state of the art does not present an algorithm which can robustly estimate the sideslip angle for vehicles with all-wheel drive. A deep learning network based sideslip angle observer is presented in this article for robust estimation of vehicle sideslip angle. The observer takes in the inputs from all the on board sensors present in a vehicle and it gives out an estimate of the sideslip angle. The observer is tested extensively using data which are obtained from proving grounds in high tire-road friction coefficient conditions.

Nowadays, the 48 V vehicle architecture seems to be the perfect bridge between the 12 V system and the costly High Voltage (HV) electrification towards the crucial goal of CO2 and pollutants emissions reduction in combination with enhanced performance. However, this approach leads to an increased complexity in the interaction between different sub-systems targeting the optimization of the Energy Management System (EMS). Therefore, it becomes essential to perform a preliminary hardware assessment, exploring the interactions between the different components and quantifying the cost vs benefit trade-off. To this purpose, an integrated experimental/numerical methodology has been adopted: a comprehensive map-based Hybrid Electric Vehicle (HEV) model has been built, allowing the simulation of a variety of hybrid architectures, including both HV and 48 V systems.

Autonomous Driving is one of the main subjects of academic research and one important trend in the automotive industry. With the advent of self-driving vehicles, the interest around trajectory planning raises, in particular when a customer-oriented analysis is performed, since more and more the carmakers will have to pay attention to the handling comfort. With that in mind, an experimental approach is proposed to assess the main characteristics of human driving and gain knowledge to enhance quality of autonomous vehicles. Focusing on overtaking maneuvers in a highway environment, four comfort indicators are proposed aiming to capture the key aspects of the chosen paths of a heterogeneous cohort. The analysis of the distribution of these indicators (peak to peak lateral acceleration, RMS lateral acceleration, Smoothness and Jerk) allowed the definition of a human drive profile.

In vehicle dynamics, simple and fast vehicle models are required, especially in the framework of real-time simulations and autonomous driving software. Therefore, a trade-off between accuracy and simulation speed must be pursued by selecting the appropriate level of detail and the corresponding simplifying assumptions based on the specific purpose of the simulation. The aim of this study is to develop a methodology for map and parameter estimation from multibody simulation results, to be used for simplified vehicle modelling focused on handling performance. In this paper, maneuvers, algorithms and results of the parameter estimation are reported, together with their integration in single track models with increasing complexity and fidelity. The agreement between the multibody model, used as reference, and four single track models is analyzed and discussed through the evaluation of the correlation index.

Flow control over aerodynamic shapes in order to achieve performance enhancements has been a lively research area for last two decades. Synthetic Jet Actuators (SJAs) are devices able to interact actively with the flow around their hosting structure by providing ejection and suction of fluid from the enclosed cavity containing a piezo-electric oscillating membrane through dedicated orifices. The research presented in this paper concerns the implementation of zero-net-mass-flux SJAs airflow control system on a NACA0015, low aspect ratio wing section prototype. Two arrays with each 10 custom-made SJAs, installed at 10% and 65% of the chord length, make up the actuation system. The sensing system consists of eleven acoustic pressure transducers distributed in the wing upper surface and on the flap, an accelerometer placed in proximity of the wing c.g. and a six-axis force balance for integral load measurement.

Vehicle dynamics is a fundamental part of vehicle performance. It combines functional requirements (i.e. road safety) with emotional content (“fun to drive”, “comfort”): this balance is what characterizes the car manufacturer (OEM) driving DNA. To reach the customer requirements on Ride & Handling, integration of CAE and testing is mandatory. Beside of cutting costs and time, simulation helps to break down vehicle requirements to component level. On chassis, the damper is the most important component, contributing to define the character of the vehicle, and it is defined late, during tuning, mainly by experienced drivers. Usually 1D lookup tables Force vs. Velocity, generated from tests like the standard VDA, are not able to describe the full behavior of the damper: different dampers display the same Force vs. Velocity curve but they can give different feeling to the driver.

The Vehicle Energy Consumption calculation Tool (VECTO) is used in Europe for calculating standardised energy consumption and CO2 emissions from Heavy-Duty Trucks (HDTs) for certification purposes. The tool requires detailed vehicle technical specifications and a series of component efficiency maps, which are difficult to retrieve for those that are outside of the manufacturing industry. In the context of quantifying HDT CO2 emissions, the Joint Research Centre (JRC) of the European Commission received VECTO simulation data of the 2016 vehicle fleet from the vehicle manufacturers. In previous work, this simulation data has been normalised to compensate for differences and issues in the quality of the input data used to run the simulations. This work, which is a continuation of the previous exercise, focuses on the deeper meaning of the data received to understand the factors contributing to energy and fuel consumption.

The application of Miller cycle through Late Intake Valve Closure (LIVC) or Early Intake Valve Closure (EIVC) for knock mitigation at high load on a turbocharged downsized spark ignition engine was experimentally investigated. By reducing the effective compression ratio due to a shorter compression stroke and hence achieving lower charge temperatures inside the cylinder, significant mitigation of knock tendency could be obtained. As a consequence, the spark advance retard could be substantially decreased and the enrichment of the mixture could significantly be reduced, thus obtaining impressive efficiency improvements. In this research, both EIVC and LIVC strategies have been examined aiming to achieve possible improvements for knock mitigation and after some preliminary investigations confirmed LIVC being more effective than EIVC for this goal, the latter was discarded and the research activities were focused on LIVC only.

The innovative highly flexible wings made of extremely light structures, yet still capable of carrying a considerable amount of non- structural weights, requires significant effort in structural simulations. The complexity involved in such design demands for simplified mathematical tools based on appropriate nonlinear structural schemes combined with reduced order models capable of predicting accurately their aero-structural behaviour. The model presented in this paper is based on a consistent nonlinear beam-wise scheme, capable of simulating the unconventional aeroelastic behaviour of flexible composite wings. The partial differential equations describing the wing dynamics are expanded up to the third order and can be used to explore the effect of static deflection imposed by external trim, the effect of gust loads and the one of nonlinear aerodynamic stall.

Nautilus S.p.A. and the Polytechnic of Turin, in cooperation with Blue Engineering, have developed a very versatile product, the ELETTRA Twin Flyers [6] (ETF), which consists in a very innovative remotely-piloted airship equipped with high precision sensors and communication devices. This multipurpose platform is particularly suitable for border and maritime surveillance missions and for telecommunication, both in military and civil area. To assess the actual maneuver capabilities of the airship [14], a prototype of reduced size and complexity has been assembled [16]. Before the flight tests a further assessment on the flight simulator is needed, because the first version of the software is tuned on the full scale prototype. Steady state performance and static stability of the demonstrator have been evaluated with CFD analysis.

This paper presents a Fuel Cell Electric Vehicle (FCEV) powertrain development and optimization, aiming to minimize hydrogen consumption. The vehicle is a prototype that run at the Shell Eco-marathon race and its powertrain is composed by a PEM fuel cell, supercapacitors and a DC electric motor. The supercapacitors serve as an energy buffer to satisfy the load peaks requested by the electric motor, allowing a smoother (and closer to a stationary application) working condition for the fuel cell. Thus, the fuel cell can achieve higher efficiency rates and the fuel consumption is minimized. Several models of the powertrain were developed using MATLAB-Simulink and then experimentally validated in laboratory and on the track. The proposed models allow to evaluate two main arrangements between fuel cell and supercapacitors: 1) through a DC/DC converter that sets the FC current to a desired value; 2) using a direct parallel connection between fuel cell and supercapacitors.

This study assesses the capabilities of dynamic wireless power transfer with respect to range extension and payload capacity of heavy-duty trucks. Currently, a strong push towards tailpipe CO2 emissions abatement in the heavy-duty transport sector by policymakers is driving the development of battery electric trucks. Yet, battery-electric heavy-duty trucks require large battery packs which may reduce the payload capacity and increase dwell time at charging stations, negatively affecting their acceptance among fleet operators. By investigating various levels of development of wireless charging technology and exploring various deployment scenarios for an electrified highway lane, the potential for a more efficient and environmentally friendly battery sizing was explored.

Simulation is becoming the fundamental tool to design the main components of a vehicle. The paper describes the shock absorber model which was implemented by the Vehicle Dynamics Research Team of Politecnico di Torino. It is a modular model which can be adopted both for mono-tube and twin-tube shock absorbers. It can be used at different levels of approximation, as a function of the kind of user and his/her targets. The main data which have to be inserted in the model are fluid properties, the basic dimensions of the component and the characteristics of the orifices of the shock absorber. An experimental test bench was conceived to obtain the diagrams plotting flow rate through an orifice of a shock absorber versus the pressure drop between input and output ports. The test rig and the procedure to perform the experimental tests and insert the results in the shock absorber model are described in detail.

Lithium Ion (Li-ion) batteries have emerged as the dominant technology for electric mobility due to their performance, stability, and long cycle life. Nevertheless, there are emerging environmental and economic issues from Li-ion batteries related to depleting critical resources and their potential shortage. This paper focuses on developing the Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) of a generic Li-ion battery pack with a Nickel-Manganese-Cobalt (NMC) cathode chemistry, being the most used, and a capacity of 95 kWh as an average between different carmakers. The LCA and LCC include all the relevant phases of the life cycle of the product. The costs related to the LCC assessment have been taken as secondary data. Lastly, the same system boundary has been chosen both for the LCA and LCC.

The ongoing global demand for greater energy efficiency plays an essential role in the automotive industry, as the focus is moving from ICEs to hybrid (HEVs) and electric (EVs) vehicles. New virtual methodologies are necessary to reduce the development effort of these technologies. In this context, the thermal management of the vehicle high voltage battery pack is becoming increasingly important, with significant impact on the vehicle’s range in different environmental scenarios. In this paper, an advanced method is proposed to compute 3D temperature distribution of the cells of a high voltage battery pack for Plug-in Hybrid (PHEV) or full electric (EV) applications. The thermal FE model of a complete PHEV vehicle was integrated with an electrical NTG equivalent circuit model of the HV battery to compute the heat loads of the cells.