Search Results (37)

This study develops a real-time energy-efficient control strategy for distributed-drive electric tractors (DDETs) to minimize electrical energy consumption during traction operations. Taking a four-wheel independently driven DDET as the research object, we conduct dynamic analysis of draft operations and establish dynamic models of individual components in the tractor’s drive and transmission system. A backpropagation (BP) neural network-based operational speed prediction model is constructed to forecast operational speed within a finite prediction horizon. Within the model predictive control (MPC) framework, a real-time energy-efficient control strategy is formulated, employing a dynamic programming algorithm for receding horizon optimization of energy consumption minimization. Through plowing operation simulation with comparative analysis against a conventional equal torque distribution strategy, the results indicate that the proposed real-time energy-efficient control strategy exhibits superior performance across all evaluation metrics, providing valuable technical guidance for future research on energy-efficient control strategies in agricultural electric vehicles. Full article

This work presents the experimental evaluation of a robotic walker following the full implementation of its sensor and motorization system. The aging population and increasing mobility impairments drive the need for assistive robotic technologies that enhance safe and independent movement. The main objective was to validate the device’s behavior in real-use scenarios by assessing its stability, responsiveness, and accuracy in detecting user movement. Tests were carried out in straight-line walking and on paths involving directional changes, both with and without motor assistance, using a cohort of five test users. Principal Component Analysis (PCA) and t-SNE dimensionality reduction techniques were applied to analyze the inertial (IMU) and proximity (TOF) sensor data, complemented by motor control monitoring through wheel Hall sensors, to explore gait patterns and system performance. Additionally, synchronized measurements between the user’s and walker’s inertial units and Time-of-Flight sensors allowed the evaluation of spatial alignment and motion correlation. The results provide a foundation for future system adjustment and optimization, ensuring the walker offers effective, safe, and adaptive assistance tailored to the user’s needs. Findings reveal that the walker successfully distinguishes individual gait patterns and adapts its behavior accordingly, demonstrating its potential for personalized mobility support. Full article

Increasing developments in the offshore energy sector have led to demand for robotics use in inspection, maintenance, and repair maintenance tasks, particularly for the service life extension of structures. These robots experience slippage due to varying surface conditions caused by environmental factors and marine growth, leading to inconsistent traction forces and potential mission failures in single-drive systems. This paper explores control strategies and mechanical configurations both in simulation and on the physical industrial robot to mitigate slippage in offshore robotic operations, improving reliability and reducing costs. This study examines mechanical and control modifications such as multi-wheel drive (MWD), PID velocity control, and a feedback-linearized slip control system with an individual wheel disturbance observer to detect surface variations. The results indicate that a 3 WD setup with slip control handles the widest range of conditions but suffers from high control effort due to chattering effects. The simulations show potential for slip control; practically, challenges arise from low sampling rates compared to traction changes. In real-world conditions, a PID-controlled MWD system, combined with increased normal force, achieves better traction and stability. The findings highlight the need for further investigation into the mechanical design and sensor feedback, with the refinement of slip control strategies and observer design for the offshore environment. Full article

This article focuses on trajectory tracking control of a four-wheeled mobile robot, with non-steered wheels. The issues in terms of robot kinematics are discussed and a dynamics model is derived, which additionally took into account the drive unit model. This paper analyses four versions of the control system, which take into account the possibility of compensating for wheel slip and non-linearities resulting from the drive unit model. It is assumed that the wheel-slip compensation is based on the measurement of the actual robot’s motion parameters. The linear and angular motion parameters of the robot’s mobile platform are taken into account, which allows for the estimation of the wheel slip velocities. The results of the simulation studies are presented, consisting of the evaluation of individual control system solutions in terms of achieving the highest possible accuracy in executing a prescribed trajectory. Additionally, the impact of the investigated control strategies on electric power demand and electric energy consumption by the robot’s drives is analyzed. In order to quantitatively assess the control system solutions, quality indexes were adopted, focusing on tracking accuracy and energy efficiency. The research results indicate that incorporating wheel-slip compensation into the control system enables high accuracy to be achieved in terms of trajectory tracking. In turn, the use of the drive unit model within the control system leads to an increase in the accuracy of the robot’s wheel movements, which does not ultimately result in an increase in the accuracy of the motion of the robot’s mobile platform due to the slipping of the wheels. It was also observed that improving the trajectory tracking accuracy leads to an increase in the maximum electric power demand and electric energy consumption by the robot’s drives. Full article

The wheels of decelerating vehicles in braking mode roll with increased slip, up to complete lock-up, which is a negative phenomenon. This is effectively managed by the anti-lock braking system (ABS). However, in the course of braking, especially before the system activation, self-excited oscillatory processes with high amplitudes may occur, causing increased dynamic loads on the drive system. The paper studies the braking processes of a vehicle with an electromechanical individual traction drive in both electrodynamic regenerative and combined braking modes, utilizing the drive and the primary braking system. The theoretical framework is provided for identifying the self-excited oscillation onset conditions and developing a technique to detect wheel slips during braking to suppress these oscillations. To check the functionality of the wheel-slip observer in braking mode, the performance of the self-excited oscillation pulse suppression algorithm was studied in the MATLAB Simulink 2018b software package. The study results can be used to develop control systems equipped with the function of suppressing self-excited oscillations by vehicle motion. Full article

It is essential and forward-thinking to investigate the personalized use of four-wheel driving and steering wire-controlled unmanned chassis. This paper introduces a personalized path-tracking approach designed to adapt the vehicle’s control system to human-like characteristics, enhancing the fit and maximizing the potential of the chassis’ multi-directional driving and steering capabilities. By modifying the classic vehicle motion controller design, this approach aligns with individual driving habits, significantly improving upon traditional path-tracking control methods that rely solely on reference vector fields. First, the classic reference vector field’s logic was expanded upon, and it is shown that a personalized upgrade is feasible. Then, driving behavior data from multiple drivers were collected using a driving simulator. The fuzzy c-means clustering method was used to categorize drivers based on typical states that match vehicle path-tracking performance. Additionally, the random forest algorithm was used as the method for recognizing driving style. Subsequently, a personalized path-tracking control strategy based on the reference vector field was developed and a distributed execution architecture for four-wheel driving and steering wire-controlled unmanned chassis was established. Finally, the proposed personalized path-tracking approach was validated using a driving simulator. The results of the experimental tests demonstrated that the personalized path-tracking control approach not only fits well with various driving styles but also delivers high accuracy in driving style identification, making it highly suitable for application in four-wheel driving and steering wire-controlled chassis. Full article

The subject of the article was the chemical analysis of gasoline and exhaust gas samples taken from an urban two-wheeled vehicle. The main aim of the work was to identify chemical compounds emitted by a group of urban two-wheeled vehicles depending on the engine’s operating parameters. First, engine operating parameters and driving parameters of three urban two-wheeled vehicles were measured in real operating conditions. Based on the averaged results, engine operating points were determined for exhaust gas samples that were collected into Tedlar bags. The exhaust gas composition of individual chemical substances obtained in the chromatographic separation process were subjected to a detailed analysis relating the engine operating point with their emission rate, with each individual component being assessed in terms of its impact on human health. The obtained qualitative analysis results indicated the presence of alkenes, alkanes, aliphatic aldehydes, and aromatic and cyclic hydrocarbons (cycloalkanes) in the tested samples. The experiments provided a variety of conclusions relating to the operating parameters of a two-wheeler engine. Qualitative assessment of exhaust samples showed that a two-wheeled vehicle was characterized by the most varying composition of BTX aromatic hydrocarbons derivatives, which are particularly dangerous to human health and life. Therefore, the authors suggest that in the future, approval procedures regarding toxic emissions should be extended to include chromatographic tests. The presented results are an extension of previous studies on toxic emissions from urban two-wheeled vehicles in real operating conditions that were published in other journals. Full article

Auto-oscillations may occur in moving vehicles in the area where the tire interacts with the support base. The parameters of such oscillations depend on the sliding velocity in the contact patch. As they negatively affect the processes occurring in the electric drive and the mechanical transmission, reducing their energy efficiency, such processes can cause failures in various elements. This paper aims to conduct a theoretical study into the peculiarities of oscillatory processes in the nonlinear system and an experimental study of the auto-oscillation modes of an individual traction drive. It presents the theoretical basis used to analyze the peculiarities of oscillation processes, including their onset and course, the results of simulation mathematical modeling and the experimental studies into the oscillation phenomena in the movement of the vehicle towards the supporting base. The practical value of this study lies in the possibility to use the results in the development of algorithms for the exclusion of auto-oscillation phenomena in the development of vehicle control systems, as well as to use the auto-oscillation processes onset and course analysis methodology to design the electric drive of the driving wheels. Full article

The surface of the Moon and planets have been covered with loose soil called regolith, and there is a risk that the rovers may stack, so it is necessary for them to recognize the traveling state such as its posture, slip behavior, and sinkage. There are several methods for recognizing the traveling state such as a system using cameras and Lidar, and they are used in real exploration missions like Mars Exploration Rovers of NASA/JPL. When a rover travels and travels across loose soil with steep slopes like a side wall of a crater on the lunar surface, the rover has side slipping. It means that its behavior makes the rover slip down to the valley direction. Even if this detection uses sensors like a camera and Lidar or other controlling systems like SLAM (Simultaneous Localization and Mapping), it would be too difficult for the rover to avoid slipping down to valley direction, because it is not able to detect the traction or resistance given from ground by individual wheel of the rover, as the traction of individual wheel of the rover is not clear. This means that the movement of the rover appeared by integrating the traction of all wheels mounted on the rover. Even if the localization by sensors is carried out, the location would be the location after slipping down. This is because when traveling on unstable ground, the driving force of each individual wheel cannot be accurately predicted, and the sum of the driving force of all wheels is the motion of the rover, which is detected after the position changes. Therefore, if the rover obtains information on the traction of each wheel, its maneuver to change its posture would work sooner and it would be able to travel more efficiently than in a state without that information. Because the onboard computer of rovers can identify their location and state from the information of the traction of each wheel, they can decide the next work carefully and in detail. From these tasks, we focused on the intrinsic sensation of a biological function like a human body and aimed to develop a system that recognizes the traveling state (slip condition) from the shape deformation of the chassis. In this study, we experimentally verified the relationship between the change in strain, which is the amount of deformation acting on the chassis, and the traveling state while the wheel is traveling. From the experimental results, we confirmed that the strain in the chassis was displaced dynamically and that the strain changed oscillatory while the wheel was traveling. In addition, based on the function of muscle spindles as mechanoreceptors, we discussed two methods of analyzing strain change: nuclear chain fiber analysis and nuclear bag fiber analysis. These analyses mean that the raw data of the strain are updated to detect the characteristic strain elements of a chassis while the wheel is traveling through loose soil. Eventually, the slipping state could be estimated by updating the data of a lot of strain raw data, and it was confirmed that the traveling state could be detected. Full article

This paper considers the problem of minimum-time smooth trajectory planning for wheeled mobile robots. The smooth path is defined by several Bézier curves and the calculated velocity profiles on individual segments are minimum-time with continuous velocity and acceleration in the joints. We describe a novel solution for the construction of a 5th order Bézier curve that enables a simple and intuitive parameterization. The proposed trajectory optimization considers environment space constraints and constraints on the velocity, acceleration, and jerk. The operation of the trajectory planning algorithm has been demonstrated in two simulations: on a racetrack and in a warehouse environment. Therefore, we have shown that the proposed path construction and trajectory generation algorithm can be applied to a constrained environment and can also be used in real-world driving scenarios. Full article

Numerical methods are often a robust way to predict how external mechanical loads affect individual biological structures. Computational models of biological systems have been developed over the years, reaching high levels of detail, complexity, and precision. In this study, two cases were analysed, differing in the airbag operation; in the first, the airbag was normally activated, and in the second case, the airbag was disabled. We analysed a model of a disabled person without a left leg who steers a vehicle using a specialized knob on the steering wheel. In both cases, a head-on collision between a car moving at an initial speed of 50 km/h and a rigid obstacle was analysed. We concluded that the activated airbag for a person with disabilities reduces the effects of asymmetries in the positioning of the belts and body support points. Moreover, all the biomechanical parameters, analysed on the 50th percentile dummy, i.e., HIC, seat belt contact force and neck injury criterion (Nij) support the use of an airbag. The resulting accelerations, measured in the head of the dummy, were induced into a finite element head model (YEAHM) to kinematically drive the head and simulate both accidents, with and without the airbag. In the latter, the subsequent head injury prediction revealed a form of contrecoup injury, more specifically cerebral contusion based on the intracranial pressure levels that were achieved. Therefore, based on the in-depth investigation, a frontal airbag can significantly lower the possibility of injuries for disabled drivers, including cerebral contusions. Full article

Brake forces and maximum static road friction coefficients for each wheel of the vehicle are essential information for vehicle safety systems including adaptive cruise control, electronic stability control (ESC), and collision avoidance system, etc. Many studies have been performed to estimate brake force and road friction using well-known model-based approaches, but none have unambiguously guaranteed an accurate performance in all ranges of driving conditions and road ones. In addition, the investigation of the integrated estimation approach of road friction and brake force including mass estimation has not been clearly addressed so far. Therefore, in this study, a novel integrated estimation strategy based on a data-driven technique and artificial neural network (ANN) classifier along with a compact mass identification has been proposed to acquire the accurate road friction and brake force of individual wheel. Specifically, it includes an instant mass estimation by monitoring static suspension deflections, an artificial neural network (ANN) classifier for road friction coefficient based on the average data set from available standard sensors, and a brake force estimation using the data-driven technique. The performance of the proposed technique is validated by a co-simulation environment between Carsim and MATLAB/Simulink. It is found that the integrated estimation strategy guaranteed an accurate estimation of brake forces and road friction for a wide range of variations of road frictions, vehicle velocities, and masses. This work will be a valuable asset for those who wish to develop an integrated estimation system for such crucial parameters of the vehicle system. Full article

Unstructured off-road environments with complex terrain obstacles and pavement properties bring obvious challenges for special purpose autonomous vehicle control. A cascade direct yaw moment control strategy (CDYC), which contains a main loop and a servo loop, is proposed to enhance the accuracy and stability of an independent eight in-wheel motor-driven autonomous vehicle with rear-wheel steering (8WD/RWS). In the main loop, double PID controllers are designed to generate the desired drive moment and yaw rate. In the servo loop, the quadratic programming (QP) algorithm with the tire force boundaries optimally allocates the demanded yaw moment to individual wheel torques. The 8WD/RWS prototype is virtually established using TruckSim and serves as the control object for co-simulation. The proposed cascade controller is verified by simulations in customized off-road driving scenarios. The simulation results show that the proposed control architecture can effectively enhance the path-tracking ability and handling stability of the 8WD/RWS, as to ensure the maneuverability and control stability under extreme off-road conditions. Full article

One of the problems limiting the off-road mobility of multi-axle-wheeled vehicles is a kinematic discrepancy, which increases the resistance to motion when negotiating obstacles. This paper presents the results of research on the possibility of reducing the kinematic discrepancy in vehicles with a hydrostatic drive for each wheel by the appropriate selection of hydraulic components—hydraulic motors and flow dividers. Four different configurations of the drivetrain were tested. They used slow-running hydraulic orbital motors and multi-piston radial motors, as well as gear and spool flow dividers. The tests were conducted with computer simulations based on tests that had already been performed to identify hydraulic parts. They allowed for the assessment of the influence of the characteristics of the components and the configuration of the drive system on the differentiation of the rotational speeds of individual wheels, slippage between the wheels and the ground, and the developed driving torques while overcoming obstacles. These values directly translate into the kinematic discrepancy of the system, the ability to overcome terrain obstacles, and energy consumption. Full article

With the availability of modern assistive techniques, ambient intelligence, and the Internet of Things (IoT), various innovative assistive environments have been developed, such as driving assistance systems (DAS), where the human driver can be provided with physical and emotional assistance. In this human–machine collaboration system, haptic interaction interfaces are commonly employed because they provide drivers with a more manageable way to interact with other components. From the view of control system theory, this is a typical closed-loop feedback control system with a human in the loop. To make such a system work effectively, both the driving behaviour factors, and the electrical–mechanical components should be considered. However, the main challenge is how to deal with the high degree of uncertainties in human behaviour. This paper aims to provide an insightful overview of the relevant work. The impact of various types of haptic assistive driving systems (haptic guidance and warning systems) on driving behaviour performance is discussed and evaluated. In addition, various driving behaviour modelling systems are extensively investigated. Furthermore, the state-of-the-art driving behaviour controllers are analysed and discussed in driver–vehicle–road systems, with potential improvements and drawbacks addressed. Finally, a prospective approach is recommended to design a robust model-free controller that accounts for uncertainties and individual differences in driving styles in a haptic assistive driving system. The outcome indicated that the haptic feedback system applied to the drivers enhanced their driving performance, lowered their response time, and reduced their mental workload compared to a system with auditory or visual signals or without any haptic system, despite some annoyances and system conflicts. The driving behaviour modelling techniques and the driving behaviour control with a haptic feedback system have shown good matching and improved the steering wheel’s base operation performance. However, mathematical principles, a statistical approach, and the lack of consideration of the individual differences in the driver–vehicle–road system make the modelling and the controller less robust and inefficient for different driving styles. Full article