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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "E: Electric Vehicles".

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 37902

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Dr. Daniel Chindamo

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Department of Mechanical and Industrial Engineering, University of Brescia, I-25123 Brescia, Italy
Interests: vehicle dynamics; HEVs
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The evolution of the automotive world towards electrification means that a variety of hybrid and electric cars with different powertrain architectures can be found on the market. In electric vehicles with a multiple-motor powertrain, a torque vectoring strategy, for instance, can be achieved with individual wheel torque control. This feature can significantly enhance the cornering response, stability, performance and active safety, whilst improving the vehicle dynamic properties of the car. Torque vectoring can also increase energy efficiency through the appropriate design of the target reference to calculate the wheel torque distribution. Moreover, typical active vehicle dynamic control strategies and active safety systems rely on the real-time monitoring of the vehicle sideslip angle (VSA), which is generally not directly measured for impracticality. VSA estimation has been a big challenge since the introduction of the very first on-board active systems, and it is still a hot research topic.

This Special Issue will focus on vehicle dynamic control strategies, aiming to increase vehicle performance/response and active safety, together with VSA estimation methods and all the vehicle models involved with them. Papers are invited in all these different areas (but are not limited to them), as they are multidisciplinary topics involving economic and environmental aspects as well. Both theoretical and experimental works are welcome, especially those including validation with real-world data or experiments. Recently, interest in driving simulators and the so-called human-in-the-loop simulations has been raised; therefore, papers exploring the utility of such a tool in developing vehicle dynamic control strategies are also encouraged.

Dr. Daniel Chindamo
Guest Editor

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Keywords

vehicle dynamics control strategies
active yaw control
torque vectoring
vehicle side-slip angle estimation
driving simulator
vehicle models
hybrid and electric vehicles

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Published Papers (11 papers)

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Research

17 pages, 7864 KiB

Open AccessArticle

Development of an Electric All-Wheel-Drive Simulation Model Used to Test Torque Distribution Algorithms

by Alexander M. Zavatsky, Andrey V. Keller, Sergey S. Shadrin, Daria A. Makarova and Yury M. Furletov

Energies 2023, 16(20), 7144; https://doi.org/10.3390/en16207144 - 19 Oct 2023

Viewed by 1172

Abstract

The paper describes the developed curvilinear motion simulation model for a vehicle with two traction electric motors moving on a solid surface used to study the dynamic properties of a wheeled vehicle and to subject the developed methods to virtual testing. The simulation model of the electric all-wheel drive vehicle is carried out in the Simcenter Amesim environment to account for the dynamic characteristics and features of the vehicle. The simulation model was developed based on the drawn requirements while the assumptions were justified. Inertia characteristics, tire characteristics, suspension elements, grip characteristics, and surface and air resistance were considered, as these factors affect the vehicle longitudinal and transverse dynamics. The article presents the model implemented in the “Labcar” system and confirms its adequacy by comparing it with the data obtained during the full-scale prototype tests. The bench and range tests of a test vehicle with electric transmission equipped with a measuring complex confirmed the adequacy of the developed model. The results of comparative tests allow for the conclusion that the developed model complex is suitable for modeling purposes, including studying, debugging and initial calibrations of the algorithm of torque distribution on the driving axles of all-wheel drive electric vehicle. Full article

(This article belongs to the Special Issue Vehicle Dynamics and Control)

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28 pages, 13440 KiB

Open AccessArticle

Different Control Techniques of Permanent Magnet Synchronous Motor with Fuzzy Logic for Electric Vehicles: Analysis, Modelling, and Comparison

by Khoudir Kakouche, Adel Oubelaid, Smail Mezani, Djamila Rekioua and Toufik Rekioua

Energies 2023, 16(7), 3116; https://doi.org/10.3390/en16073116 - 29 Mar 2023

Cited by 20 | Viewed by 6367

Abstract

This paper presents a detailed analysis and comparative study of three torque control methodologies with fuzzy logic, namely direct torque control (DTC), fuzzy direct torque control (FDTC), and model predictive direct torque control (MPDTC), for PMSM control applied to an electric vehicle. The three control strategies are designed and developed to control torque in order to achieve vehicle requirements, such as minimum torque and flux ripples, fast dynamic response, and maximum efficiency. To enhance the performance and efficiency of the overall drive, a bidirectional DC/DC buck-boost converter is connected to the Li-ion battery. In addition, a fuzzy logic controller (FLC) is used in the outer loop to control the speed of the PMSM. As a result, the tuning difficulty of the conventional proportional-integral (PI) controller is avoided and the dynamic speed response is improved. Simulation results obtained from the three control techniques establish that the proposed system via the MPDTC technique reduces the torque ripples, flux ripples, reduces the THD of the PMSM current, and achieves a faster transient response. Additionally, the MPTDC technique enabled the electric vehicle to cover the longest distance, with approximately 110.72 km in a charging cycle. The real-time simulation is developed using the RT LAB simulator, and the obtained results confirm the superiority of the MPDTC technique over conventional DTC and FDTC techniques. Full article

(This article belongs to the Special Issue Vehicle Dynamics and Control)

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24 pages, 20644 KiB

Open AccessArticle

A Concept for Using Road Wetness Information in an All-Wheel-Drive Control

by Georg Warth, Philipp Sieberg, Michael Unterreiner and Dieter Schramm

Energies 2022, 15(4), 1284; https://doi.org/10.3390/en15041284 - 10 Feb 2022

Cited by 1 | Viewed by 1951

Abstract

This paper presents a concept for using road wetness information in an all-wheel-drive (AWD) control that distributes drive torques in the longitudinal direction. Driving on wet roads requires special attention. Not only does the road surface friction coefficient decrease, but driving dynamics targets must be adjusted to prevent vehicle instability under wet conditions. As an exemplary application, the otherwise generic control concept is implemented on an AWD vehicle with a torque-on-demand transfer case. Therefore, the AWD topology of a drive train with a torque-on-demand transfer case is analysed in advance in terms of occurring torques and rotational speeds. In the following, the vehicle dynamics goals for driving in wet road conditions are described—divided into primary and secondary goals. Starting from a state-of-the art AWD control, an adaptive control strategy is derived by superimposing a wetness coordination unit. With the knowledge of occurring road wetness, this unit adapts newly introduced parameters in order to meet the target driving behaviour under wet conditions. Lastly, the derived AWD control is implemented into a 14-DOF, non-linear vehicle model in Matlab/Simulink, which is used as a virtual plant. The performance of the developed concept is assessed by the driving maneuver “Power On Cornering“ (PON), which means an acceleration out of steady-state circular motion. As its essential benefit, the AWD control enables a maximum spread between driving stability, agility and traction under combined dynamics when using wetness information. The newly introduced wetness coordination unit uses only a few additional and physically interpretable key parameters for this purpose, without significantly increasing the controller complexity. Full article

(This article belongs to the Special Issue Vehicle Dynamics and Control)

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16 pages, 3209 KiB

Open AccessArticle

Yaw Stability Research of the Distributed Drive Electric Bus by Adaptive Fuzzy Sliding Mode Control

by Jiming Lin, Teng Zou, Feng Zhang and Yong Zhang

Energies 2022, 15(4), 1280; https://doi.org/10.3390/en15041280 - 10 Feb 2022

Cited by 13 | Viewed by 2560

Abstract

The direct yaw moment control can effectively enhance the yaw stability of the vehicle under extreme conditions, which has become one of the essential technologies for the distributed driving electric bus. Due to the features of a large mass and high center of gravity of the bus, lateral instability is more likely to occur under extreme driving conditions. To reduce the uncertainty and interference in the yaw movement process of the bus, this paper targets the instability caused by the coupling problem between the sideslip angle and yaw rate. An adaptive fuzzy sliding mode control is proposed to execute direct yaw moment control. The weight coefficient of the sideslip angle and the yaw rate is adjusted via fuzzy control in real time. The optimal direct yaw moment is finally obtained. A distribution method based on the vertical load proportion is adopted for the allocation of four motors’ torque. Under three typical working conditions, a joint simulation test was carried out. The simulation results demonstrate that the raised method decreases the amplitude of the sideslip angle by 20.90%, 12.75%, and 23.67% and the yaw rate is 8.62%, 6.89%, and 9.28%, respectively. The chattering and sudden changes in the additional yaw moment are also lessened. The control strategy can realize the control target, which effectively strengthens the yaw stability of the bus. Full article

(This article belongs to the Special Issue Vehicle Dynamics and Control)

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19 pages, 4497 KiB

Open AccessArticle

Model Predictive Control Based Path Tracking and Velocity Control with Rollover Prevention Function for Autonomous Electric Road Sweeper

by Yonghwan Jeong, Wongun Kim and Seongjin Yim

Energies 2022, 15(3), 984; https://doi.org/10.3390/en15030984 - 28 Jan 2022

Cited by 6 | Viewed by 3584

Abstract

This paper presents a model predictive control (MPC)-based algorithm for rollover prevention of an autonomous electric road sweeper (AERS). For AERS, the basic function of autonomous driving is a path- and velocity-tracking control needed to make a vehicle follow given path and velocity profiles. On the other, the AERS adopts an articulated frame steering (AFS) mechanism which can make cornering behavior agile. Moreover, the tread of the AERS is narrow, and the height of the mass center is high. As a result, it is prone to roll over. For this reason, it is necessary to design a controller for path and velocity tracking and rollover prevention in order to improve maneuverability and roll safety of the AERS. A kinematic model was adopted as a vehicle one for the AERS. With the vehicle model, reference states of position and velocity were determined that are needed to make the AERS track the reference path and prevent rollover. With the vehicle model and reference states, an MPC-based motion controller was designed to optimize articulation angle and velocity commands. The load-transfer ratio (LTR) was used to measure a rollover propensity. To evaluate the proposed algorithm, a simulation was conducted for the U-turn scenario. Simulation results show that the proposed algorithm improves path tracking and prevents the rollover of the AERS. Full article

(This article belongs to the Special Issue Vehicle Dynamics and Control)

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15 pages, 9673 KiB

Open AccessArticle

Innovative Energy-Saving Propulsion System for Low-Speed Biomimetic Underwater Vehicles

by Paweł Piskur, Piotr Szymak, Michał Przybylski, Krzysztof Naus, Krzysztof Jaskólski and Mariusz Żokowski

Energies 2021, 14(24), 8418; https://doi.org/10.3390/en14248418 - 14 Dec 2021

Cited by 16 | Viewed by 3576

Abstract

This article covers research on an innovative propulsion system design for a Biomimetic Unmanned Underwater Vehicle (BUUV) operating at low speeds. The experiment was conducted on a laboratory test water tunnel equipped with specialised sensor equipment to assess the Fluid-Structure Interaction (FSI) and energy consumption of two different types of propulsion systems. The experimental data contrast the undulating with the drag-based propulsion system. The additional joint in the drag-based propulsion system is intended to increase thrust and decrease energy input. The tests were conducted at a variety of fins oscillation frequencies and fluid velocities. The experiments demonstrate that, in the region of low-speed forward movement, the efficiency of the propulsion system with the additional joint is greater. Full article

(This article belongs to the Special Issue Vehicle Dynamics and Control)

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20 pages, 3044 KiB

Open AccessArticle

Design of Static Output Feedback and Structured Controllers for Active Suspension with Quarter-Car Model

by Manbok Park and Seongjin Yim

Energies 2021, 14(24), 8231; https://doi.org/10.3390/en14248231 - 7 Dec 2021

Cited by 17 | Viewed by 3034

Abstract

This paper presents a method to design active suspension controllers for a 7-Degree-of-Freedom (DOF) full-car (FC) model from controllers designed with a 2-DOF quarter-car (QC) one. A linear quadratic regulator (LQR) with 7-DOF FC model has been widely used for active suspension control. However, it is too hard to implement the LQR in real vehicles because it requires so many state variables to be precisely measured and has so many elements to be implemented in the gain matrix of the LQR. To cope with the problem, a 2-DOF QC model describing vertical motions of sprung and unsprung masses is adopted for controller design. LQR designed with the QC model has a simpler structure and much smaller number of gain elements than that designed with the FC one. In this paper, several controllers for the FC model are derived from LQR designed with the QC model. These controllers can give equivalent or better performance than that designed with the FC model in terms of ride comfort. In order to use available sensor signals instead of using full-state feedback for active suspension control, LQ static output feedback (SOF) and linear quadratic Gaussian (LQG) controllers are designed with the QC model. From these controllers, observer-based controllers for the FC model are also derived. To verify the performance of the controllers for the FC model derived from LQR and LQ SOF ones designed with the QC model, frequency domain analysis is undertaken. From the analysis, it is confirmed that the controllers for the FC model derived from LQ and LQ SOF ones designed with the QC model can give equivalent performance to those designed with the FC one in terms of ride comfort. Full article

(This article belongs to the Special Issue Vehicle Dynamics and Control)

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15 pages, 4339 KiB

Open AccessArticle

Automatic Clutch Engagement Control for Parallel Hybrid Electric Vehicle

by Trieu Minh Vu, Reza Moezzi, Jindrich Cyrus, Jaroslav Hlava and Michal Petru

Energies 2021, 14(21), 7256; https://doi.org/10.3390/en14217256 - 3 Nov 2021

Cited by 6 | Viewed by 3227

Abstract

Automatic clutch engagement control is essential for all kinds of vehicle power transmissions. The controllers for vehicle power transmissions may include model-based or model-free approaches and must provide high transmission efficiency, fast engagement and low jerk. Most vehicle automatic transmissions are using torque converters with transmission efficiencies up to 96%. This paper presents the use of fuzzy logic control for a dry clutch in parallel hybrid electric vehicles. This controller can minimize the loss of power transmission since it can offer a higher transmission efficiency, up to 99%, with faster engagement, lower jerk and, thus, higher driving comfortability with lower cost. Fuzzy logic control is one of the model-free schemes. It can be combined with AI algorithms, neuro networks and virtual reality technologies in future development. Fuzzy logic control can avoid the complex modelling while maintaining the system’s high stability amid uncertainties and imprecise information. Experiments show that fuzzy logic can reduce the clutch slip and vibration. The new system provides 2% faster engagement speed than the torque converter and eliminates 70% of noise and vibration less than the manual transmission clutch. Full article

(This article belongs to the Special Issue Vehicle Dynamics and Control)

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14 pages, 3589 KiB

Open AccessArticle

Sensitivity of Racing Tire Sliding Energy to Major Setup Changes: An Estimate Based on Standard Sensors

by Daniel Chindamo, Marco Gadola, Emanuele Bonera and Paolo Magri

Energies 2021, 14(16), 5118; https://doi.org/10.3390/en14165118 - 19 Aug 2021

Cited by 2 | Viewed by 4080

Abstract

Understanding the amount of energy a tire is subjected to is one of the key elements to perform in motorsport competitions, especially in Formula 1 feeder categories, where the number of tires is limited over the race weekend to contain costs. This forces teams to use worn tires towards the end of the event. Therefore, tires are usually chosen only relying on their external shape or based on the kilometers traveled. Moreover, being aware of how a setup change impacts tires can be a breakthrough in tire management, especially in tracks where tire wear is limiting the overall performance. This paper provides a scientific method aimed at helping race engineers in tire management to maintain a high performance level through the entire race weekend. Full article

(This article belongs to the Special Issue Vehicle Dynamics and Control)

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28 pages, 9444 KiB

Open AccessArticle

Enhancement of Induction Motor Dynamics Using a Novel Sensorless Predictive Control Algorithm

by Hamdi Echeikh, Mahmoud A. Mossa, Nguyen Vu Quynh, Abdelsalam A. Ahmed and Hassan Haes Alhelou

Energies 2021, 14(14), 4377; https://doi.org/10.3390/en14144377 - 20 Jul 2021

Cited by 5 | Viewed by 2657

Abstract

The paper introduces a novel predictive voltage control (PVC) procedure for a sensorless induction motor (IM) drive. In the constructed PVC scheme, the direct and quadrature (d-q) components of applied voltages are primarily managed instead of controlling the torque and flux as in the classic predictive torque control (PTC) technique. The theoretical basis of the designed PVC is presented and explained in detail, starting from the used cost-function with its relevant components. A comprehensive performance comparison is established between the two controllers, from which the superiorities of the designed PVC over the PTC approach can be easily investigated through the reduced ripples, reduced computation time, and faster dynamics. To sustain the system’s reliability, a combined Luenberger–sliding mode observer (L-SMO) is designed and verified for different operating speeds for the two controllers. The Luenberger component is concerned with estimating the stator current, rotor flux, and rotor speed. Meanwhile, the sliding mode term is used to ensure the system’s robustness against any disturbance. The verification of PVC’s validity is outlined through performing a performance analysis using the Matlab/Simulink software. The results illustrate that the IM dynamic is significantly improved when considering the constructed PVC compared with the IM dynamics under the PTC. In addition, the designed L-SMO observer has effectively proved its ability to achieve definite parameters and variable estimation. Full article

(This article belongs to the Special Issue Vehicle Dynamics and Control)

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35 pages, 7417 KiB

Open AccessArticle

Longitudinal Dynamics Simulation Tool for Hybrid APU and Full Electric Vehicle

by Giulia Sandrini, Marco Gadola and Daniel Chindamo

Energies 2021, 14(4), 1207; https://doi.org/10.3390/en14041207 - 23 Feb 2021

Cited by 10 | Viewed by 3238

Abstract

Due to problems related to environmental pollution and fossil fuels consumption that have not infinite availability, the automotive sector is increasingly moving towards electric powertrains. The most limiting aspect of this category of vehicles is certainly the battery pack, regarding the difficulty in obtaining high range with good performance and low weights. The aim of this work is to provide a simulation tool, which allows for the analysis of the performance of different types of electric and hybrid powertrains, concerning both mechanical and electrical aspects. Through this model it is possible to test different vehicle configurations before prototype realization or to investigate the impact that subsystems’ modifications may have on a vehicle under development. This will allow to speed-up the model-based design process typical for fully electric and hybrid vehicles. The model aims to be at the same time complete but simple enough to lower the simulation time and computational burden so that it can be used in real-time applications, such as driving simulators. All this reduces the time and costs of vehicle design. Validation is also provided, based on a real vehicle and comparison with another consolidated simulation tool. Maximum error on mechanical quantities is proved to be within 5% while on electrical quantities it is always lower than 10%. Full article

(This article belongs to the Special Issue Vehicle Dynamics and Control)

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