• Energy Research

This paper presents a tradeoff analysis in terms of accuracy and computational cost between different architectures of artificial neural networks for the State of Charge (SOC) estimation of lithium batteries in hybrid and electric vehicles. The considered layouts are partly selected from the literature on SOC estimation, and partly are novel proposals that have been demonstrated to be effective in executing estimation tasks in other engineering fields. One of the architectures, the Nonlinear Autoregressive Neural Network with Exogenous Input (NARX), is presented with an unconventional layout that exploits a preliminary routine, which allows setting of the feedback initial value to avoid estimation divergence. The presented solutions are compared in terms of estimation accuracy, duration of the training process, robustness to the noise in the current measurement, and to the inaccuracy on the initial estimation. Moreover, the algorithms are implemented on an electronic control unit in serial communication with a computer, which emulates a real vehicle, so as to compare their computational costs. The proposed unconventional NARX architecture outperforms the other solutions. The battery pack that is used to design and test the networks is a 20 kW pack for a mild hybrid electric vehicle, whilst the adopted training, validation and test datasets are obtained from the driving cycles of a real car and from standard profiles.

Recent studies show that hybrid powertrains with dual clutch transmission are becoming more common. This is mainly influenced by the fact that they have higher efficiency, allow power-on shifting, and are more compact. However, the electric motor attached to the primary shaft of the transmission might represent some critical issues in statics and dynamics due to additional torque, inertia, and working irregularities. This paper aims to investigate the influence of the electric motor integration in the transmission on the reliability of the overall system. The focus is on the investigation of potential over stresses of the ICE bearings due to the bending of the gearbox primary shaft. To achieve the aim, the static and the rotor dynamic analysis of the inner and outer primary shafts is performed. The numerical analyses show the potential critical issues that can arise from the excessive manufacturing and assembling tolerances, the interaction of the e-machine torque irregularities and inertia with the bending dynamics of the primary shafts.

Electrodynamic bearings exploit repulsive forces due to eddy currents to produce positive stiffness by passive means. Such a feature would make this type of bearing a viable alternative to active and permanent magnet bearings. Although electrodynamic bearings do not violate Earnshaw’s theorem, the open issue remains the stabilization system that is needed to make the rotating body stable, due to the low rotational speeds. Stabilizing solutions proposed in the literature are partially effective and not totally convincing. This limits real industrial applications. The present paper proposes a combination of electrodynamic and active magnetic bearings. At low speed the active part behaves as a conventional active magnetic bearing, while at high speed it provides damping. The readiness of the proposed solution is demonstrated by experimental results obtained using a dedicate test rig.

Abstract This paper presents a technique based on the probabilistic road map algorithm for trajectory planning in autonomous driving. The objective is to provide an algorithm allowing to compute the trajectory of the vehicle by reducing the distance traveled and minimizing the lateral deviation and relative yaw angle of the vehicle with respect to the reference trajectory, while maximizing its longitudinal speed. The vehicle is considered as a 3 Degree-of-Freedom bicycle model and a Model Predictive Control algorithm is implemented to control the lateral and longitudinal dynamics. Both the control and trajectory generation algorithms take the road lane boundaries as the only input from the surrounding environment exploiting a simulated camera. The performance of the technique is compared with the case in which the reference trajectory is the central line between the lane boundaries. The proposed algorithm is validated in a simulated driving scenario.

This paper investigates the economic viability of replacing the high-voltage battery pack of a power-split hybrid electric vehicle (HEV) and a plug-in hybrid electric vehicle (PHEV) by estimating the impact of battery ageing on the fuel economy, drivability capability and electric range. The HEV is modelled first, an optimal energy management strategy based on dynamic programming is then implemented, and experimental characterization data for the battery cell is presented. The batteries are tested to a heavily aged state, with up to an 84% loss of capacity. The battery pack payback period is estimated by assessing the vehicle operative costs in terms of fuel and electricity as obtained through numerical simulations as a function of battery ageing. Replacing the battery pack at the conventional end-of-life limit of 80% residual capacity is suggested not to be convenient from an economic standpoint for both the HEV and the PHEV. On the other hand, acceptable payback periods (i.e. 2 to 5 years) can be achieved for the battery pack when being replaced at 20% to 40% residual capacity. The proposed methodology can be implemented to advise an HEV or PHEV user regarding the benefit of replacing the battery pack due to excessive ageing.

The paper investigates the effect of tire inflation pressure on the lateral dynamics of a passenger car, and presents a possible control-oriented methodology aimed at adapting tire pressure to the current vehicle loading condition targeting a reference characteristic. Starting from the tire characteristics at several inflation pressure levels, the paper investigates the effect of changing selectively tire pressure on each of the two axles, through theoretical calculation of the curvature gain based on the computation of the derivatives of stability, and compares the obtained sensitivity to the results of a multibody simulation model validated through on-track tests. Finally, the work presents a possible algorithm that could be implemented on-board vehicle ECU to provide, for the current loading condition of the vehicle, a tire pressure combination that targets a specific lateral dynamics characteristic. The algorithm is intended as part of the control logic of an intelligent Central Tire Inflation System (CTIS) able to adjust automatically tire pressure according to the actual vehicle working conditions.

This study addresses the optimized design of electro-hydrostatic regenerative shock absorbers to enhance vibrational energy recovery in ground vehicles, aiming to reduce carbon footprint. The design strategy focuses on maximizing regeneration efficiency while minimizing actuator volume. Important trade-offs are considered as constraints, such as ride comfort and road holding. The approach employs a multi-objective evolutionary genetic algorithm, validated through numerical analysis, and applied to design a prototype. Experimental results show a peak regeneration efficiency of 45%, and simulations on a class-B vehicle indicate an average regenerated power of 101 W per shock absorber, corresponding to a CO2 emission reduction of 5.25 g/km.

Abstract The constant need to reduce emissions in the automotive sector has driven the electrification of powertrain and chassis. To comply with this trend and decrease the bound even further, the present paper proposes the use of hydraulic regenerative shock absorbers for automotive suspension systems. The conversion of linear into angular motion and the suitable control of an integrated electric machine allow to transform part of the vibrational energy into electricity. In these damping devices, the key element is the motor-pump unit that is interfaced onto a conventional hydraulic cylinder architecture. Hence, the proposed research focuses on this component by investigating different design aspects in all the domains of interest. The objective is to optimize the energy conversion efficiency of the unit without affecting its damping control property. To give means of validation, a motor-pump prototype is built and experimentally characterized through a dedicated test rig.