Vehicle Operations

The scope of this study is to demonstrate that on-board electric powertrains with torsional dynamics of the half-shafts have the potential for effective compensation, thanks to the road profile preview. This paper presents a proof-of-concept nonlinear model predictive controller (NMPC) with road preview, which is assessed with a validated simulation model of an all-wheel drive electric vehicle. Three powertrain layouts are considered, with four in-wheel, four on-board, and two on-board electric machines. The control function is evaluated along multiple manoeuvres, through comfort-related key performance indicators (KPIs) that, for the four on-board layout along a road step test at 40 km/h, highlight >80% improvements. Finally, the real-time implementability of the algorithms is demonstrated, and preliminary experiments are conducted on an electric quadricycle prototype, with more than halved oscillations of the relevant variables.

The introduction of active safety systems and advanced driver assistance systems has enhanced the control authority over the vehicle dynamics through specialized actuators, enabling, for instance, independent wheel torque control. During emergency situations, these systems step in to aid the driver by limiting vehicle response to a stable and controllable range of low longitudinal tire slips and slip angles. This approach makes vehicle behavior predictable and manageable for the average human driver; however, it is conservative in case of driving automation. In fact, past research has shown that exceeding the operational boundaries of conventional active safety systems enables trajectories that are otherwise unattainable. 

This paper presents a nonlinear model predictive controller (NMPC) for path tracking (PT), which integrates steering, front-to-total longitudinal tire force distribution, and direct yaw moment actuation, and can operate beyond the limit of handling, e.g., to induce drift, if this is beneficial to PT. Simulation results of emergency conditions in an intersection scenario highlight that the proposed solution provides significant safety improvements, when compared to the concurrent operation of PT algorithms and the current generation of vehicle stability controllers.

State-of-the-art antilock braking systems (ABS) are reactive, i.e., they activate after detecting that wheels tend to lock in braking. With vehicle-to-everything (V2X) connectivity becoming a reality, it will be possible to gather information on the tire–road friction conditions ahead, and use these data to enhance wheel slip control performance, especially during abrupt friction level variations. This study presents a nonlinear model predictive controller (NMPC) for ABS with preview of the tire–road friction profile. The potential benefits, optimal prediction horizon, and robustness of the preview algorithm are evaluated for different dynamic characteristics of the brake actuation system, through an experimentally validated simulation model. Proof-of-concept experiments with an electric vehicle prototype highlight the real-time capability of the proposed NMPC ABS, and the associated wheel slip control performance improvements in braking maneuvers with high-to-low friction transitions.

V2X connectivity and powertrain electrification are emerging trends in the automotive sector, which enable the implementation of new control solutions. Most of the production electric vehicles have centralized powertrain architectures consisting of a single central on-board motor, a single-speed transmission, an open differential, half-shafts, and constant velocity joints. The torsional drivetrain dynamics and wheel dynamics are influenced by the open differential, especially in split-μμ scenarios, i.e., with different tire-road friction coefficients on the two wheels of the same axle, and are attenuated by the so-called anti-jerk controllers. Although a rather extensive literature discusses traction control formulations for individual wheel slip control, there is a knowledge gap on: a) model based traction controllers for centralized powertrains; and b) traction controllers using the preview of the expected tire-road friction condition ahead, e.g., obtained through V2X, for enhancing the wheel slip tracking performance. This study presents nonlinear model predictive control formulations for traction control and anti-jerk control in electric powertrains with central motor and open differential, and benefitting from the preview of the tire-road friction level. The simulation results in straight line and cornering conditions, obtained with an experimentally validated vehicle model, as well as the proof-of-concept experiments on an electric quadricycle prototype, highlight the benefits of the novel controllers.

V2X technologies will become widespread in the next generation of passenger cars, and enable the development of novel vehicle control functionalities. Although a wide literature describes the energy efficiency benefits of V2X connectivity, e.g., in terms of vehicle speed profiling and platooning, there is a gap in the analysis of the potential of vehicle connectivity in enhancing the performance of active safety control systems. To highlight the impact vehicle connectivity could have on future active safety systems, this paper presents two novel control functions for connected vehicles, benefitting from the precise knowledge of the expected path and tire-road friction conditions ahead, as well as the current position of the ego vehicle. These functions, developed within recent and ongoing European projects, are: i) pre-emptive traction control; and ii) pre-emptive braking control. 

Electric vehicles (EVs) are vital in the transition toward a sustainable and carbon-neutral future. However, the widespread adoption of EVs currently depends on the convenience of the charging process and the availability of their charging infrastructure. Consequently, onboard chargers (OBCs), offering an ac-charging solution built into most EVs, have gained significant attention. Furthermore, bidirectional OBCs enable reverse power flow, whereby the EV battery can be used to power various devices, homes, or even the electric grid. However, as the trend towards bidirectional OBCs becomes evident, new power converter design challenges arise, intensifying the need for high-efficiency, compact and cost-competitive solutions. This article extensively reviews the state-of-the-art bidirectional on-board chargers by analyzing over 500 publications, identifying the key trends, challenges, and research opportunities that will influence the development of next-generation bidirectional OBCs. Hence, various strategies to achieve cutting-edge performance are deducted. This includes the rise of high-voltage batteries, the integration of powertrains, the growing adoption of wide-bandgap semiconductors, and the use of integrated planar magnetic components, all aiming to enhance efficiency and power density. This article is accompanied by a CSV file recording all pertinent references to support future research, statistical analysis, and other contributions.

The design of high-frequency transformers plays a pivotal role in electric vehicle charging systems, acting as the core component in isolated DC-DC converters. Achieving a transformer that not only operates well within the converter but also achieves high efficiency and compact size involves the balancing of numerous trade-offs. Managing the magnetic losses is essential as they dictate the efficiency but also govern the required transformer size for effective heat dissipation. This paper presents a novel transformer design method based on an exhaustive search algorithm that identifies the Pareto optimal transformers with minimised loss and weight. By introducing a Steinmetz equation filter, rapid computational speed and accuracy are combined. Loss estimations are based on experimentally validated analytical models, and the proposed methodology is experimentally validated by multiple transformer prototypes. Their operation in a dual active bridge is demonstrated by experimental measurements and circuit simulation. The results prove the effectiveness of the proposed design approach in achieving efficient and compact transformers.