Search Results (21)

Trajectory tracking is a crucial task for autonomous mobile robots, requiring smooth and safe execution in dynamic environments. This study uses a nonlinear model predictive controller (MPC) to ensure accurate trajectory tracking of a four-wheel drive, four-wheel steer (4WD-4WS) mobile robot. However, the MPC’s performance depends on the optimal tuning of its key parameters, a challenge addressed using the Multivariate Gaussian Mixture Model Continuous Ant Colony Optimization (MGMM-${\mathrm{ACO}}_R$) algorithm. This method improves on the classic ${\mathrm{ACO}}_R$ algorithm by overcoming two major limitations: the lack of consideration for interdependencies between optimized variables, and an inadequate balance between global exploration and local exploitation. The proposed approach is validated by a two-phase evaluation. Firstly, benchmark function evaluations demonstrate its superiority over established optimization algorithms, including ACO, ${\mathrm{ACO}}_R$, and PSO and its variants, in terms of convergence speed and solution accuracy. Secondly, MGMM-${\mathrm{ACO}}_R$ is integrated into the MPC framework and tested in various scenarios, including trajectory tracking with circular and eight trajectories and dynamic obstacle avoidance during trajectory tracking. The results, evaluated based on trajectory error, control effort, and computational latency, confirm the robustness of the proposed method. In particular, the explicit modeling of correlations between variables in MGMM-${\mathrm{ACO}}_R$ guarantees stable, collision-free trajectory tracking, outperforming conventional ${\mathrm{ACO}}_R$-based approaches that optimize variables independently. Full article

Based on the mobility requirements of electric vehicles, four-wheel drive (4WD) can significantly enhance driving capability and increase operational flexibility in handling. If the output of different drive motors can be effectively controlled, energy losses during the distribution process can be reduced, thereby greatly improving overall efficiency. This study presents a simulation platform for an electric vehicle with four motors as power sources. This platform also consists of the driving cycle, driver, lithium-ion battery, vehicle dynamics, and energy management system models. Two rapid-prototyping controllers integrated with the required circuit to process analog-to-digital signal conversion for input and output are utilized to carry out a hardware-in-the-loop (HIL) simulation. The driving cycle, called NEDC (New European Driving Cycle), and FTP-75 (Federal Test Procedure 75) are used for evaluating the performance characteristics and response relationship among subsystems. A control strategy, called ECMS (Equivalent Consumption Minimization Strategy), is simulated and compared with the four-wheel average torque mode. The ECMS method considers different demanded powers and motor speeds, evaluating various drive motor power distribution combinations to search for motor power consumption and find the minimum value. As a result, it can identify the global optimal solution. Simulation results indicate that, compared to the average torque mode and rule-based control, in the pure simulation environment and HIL simulation during the UDDS driving cycle, the maximum improvement rates for pure electric energy efficiency for the 45 kW and 95 kW power systems are 6.1% and 6.0%, respectively. In the HIL simulation during the FTP-75 driving cycle, the maximum improvement rates for pure electric energy efficiency for the 45 kW and 95 kW power systems are 5.1% and 4.8%, respectively. Full article

The aim of this study is to design and manufacture a multi-plate clutch system that uses magnetorheological (MR) fluid control to allow for a variable power transmission ratio in power distribution systems. MR fluid is a smart material that enables presenting a solution to the shocks and power loss that occur due to mechanical problems in power distribution systems. As such, the longitudinal and lateral dynamic properties of 4WD (four-wheel drive) vehicles were examined and analyzed to develop an algorithm to control the front/rear power distribution according to the road surface state and driving conditions. To verify the algorithm, the CarSim vehicle dynamics simulation program was adopted to perform experiments to understand the vehicle’s dynamic performance improvements and turning stability via a HILS (Hardware in the Loop) system. In this study, an MR fluid, multi-plate clutch was used that combines a dry clutch and a wet clutch using the characteristics of the MR fluid. Such a clutch was designed to enable continuous and smooth torque transmission by utilizing the strengths of each of the dry and wet clutches. The CarSim vehicle dynamics program was used to conduct the experiments, which were conducted by linking to the manufactured MR fluid clutch experimental device. The experiments investigated the dynamic performance based on the power distribution ratio by performing longitudinal flat, inclined driving and lateral DLC (double lane change) driving. In summary, this study found that it is possible to perform power transmission by applying a current to an MR fluid and forming a magnetic field to change the flow properties of the fluid to control the torque transmission ratio that occurs in an MR fluid clutch. Full article

Advanced driving algorithms, control strategies, and their optimization in self-driving vehicles in various scenarios are hotspots in current research; 4WS-4WD (four-wheel steering and four-wheel drive) is another hotspot in the study of new concept models; and the nonlinear dynamic characteristics of self-driving vehicles (AVs) are prominent in the fast cornering mode, which leads to a significant reduction in the accuracy and stability of trajectory tracking. Based on these research backgrounds, this paper proposes a control strategy optimization idea based on the 4WS4WD vehicle and its optimization model. The main content includes the establishment of a 3D vehicle model that takes into account vehicle load transfer and position change, and the establishment of a hierarchical control strategy based on the optimized NMPC and 4WS4WD models. The controller consists of two parts: an upper tracking controller based on the new vehicle model and NMPC, and a lower decoupled controller. The tracking control effect of the algorithmic control strategy based on the model and controller is validated in the high-speed serpentine motion mode and double-shift linear motion mode on the joint simulation platform of Car Sim and Simulink. Full article

Hybrid electric vehicle technology (HEVT) is emerging as a reliable alternative to reduce the constraints of battery-only driven pure electric vehicles (EVs). HVET utilizes an electric motor as well as an internal combustion engine for its operation. These components would work on battery power and fossil fuels, respectively, as a source of energy for vehicle mobility. The power is delivered either from battery or fuel or both sources based on user requirements, road conditions, etc. HEVT uses three major propelling systems, namely, front-wheel drive (FWD), rear-wheel drive (RWD), and four-wheel drive (4WD). In these propelling systems, the 4WD model provides torque to all four wheels at the same time. It uses all four wheels to propel thereby offering better driving capability, better traction, and a strong grip on the surface. The 4WD-based HEVs comprise four architectures, namely, series, parallel, series-parallel, and complex. The literature focuses primarily on any one type of architecture for analysis in the context of component optimization, fuel reduction, and energy management. However, a focus on dynamic analysis that gives a real performance insight was not conducted, which is the main motivation for this paper. The proposed work provides an extensive critical performance analysis of all four 4WD architectures subjected to various dynamic operating conditions (continuous, pulse, and step-up accelerations). Under these conditions, various performance parameters such as speed (of vehicle, engine, and motor), power (of engine and battery), battery electrical losses, charge patterns, and fuel consumption are measured and compared. Further, the 4WD architecture performance is validated with FWD and RWD architectures. From MATLAB/Simulink-based evaluation, 4WD HEV architectures have shown superior performance in most of the cases when compared to FWD type and RWD type HEVs. Moreover, 4WD parallel HEV architecture has shown superior performance compared to 4WD series, 4WD series-parallel, and 4WD complex architectures. Full article

Energy management strategies are vitally important to give full play to the energy-saving of the four-wheel drive electric vehicle (4WD EV). The cooperative output of multi-power components is involved in the process of driving and braking energy recovery of 4WD EV. This paper proposes a novel energy management strategy of dual equivalent consumption minimization strategy (D-ECMS) to improve the economy of the vehicle. According to the different driving and braking states of the vehicle, D-ECMS can realize the proportional control of the energy cooperative output among the multi-power components. Under the premise of satisfying the dynamic performance of the vehicle, the operating points of the power components are distributed more in the high-efficiency range, and the economy and driving range of the vehicle are optimized. In order to achieve the effectiveness of D-ECMS, MATLAB/Simulink is used to realize the simulation of the vehicle. Compared with the rule-based strategy, the economy of D-ECMS increased by 4.35%. Full article

Selecting the appropriate tyre configuration and settings for heavy farm vehicles is important to ensure that soil compaction and power loss in rolling resistance are minimised and traction is optimised. This study investigated the effect of front-wheel assist (FWA, ≈75 kN) and four-wheel drive (4 WD, ≈100 kN) tractors fitted with different tyre configurations (single, dual), tyre sizes and inflation pressures on soil strength (a proxy for soil compaction), and rolling resistance. Single-pass tests were performed on a Typic Argiudoll (≈23% clay, bulk density: 1305 kg m⁻³) managed under permanent no-tillage. Results showed that average power losses in rolling resistance were 7.5 kN and 5 kN for the 4 WD and FWA tractors, respectively. The average rut depth increased by approximately 1.4 times after a pass of the 4 WD compared with the FWA tractor. The soil cone index (0–600 mm depth) increased from 2023 kPa (before traffic) to 2188 and 2435 kPa after single passes of the FWA and 4WD tractors, respectively (p < 0.05). At the centreline of the tyre rut, dual tyres reduced the soil cone index a little compared with single tyres, but they significantly increased the volume of soil over which soil strength, and therefore soil compaction, was increased. For both tractors (regardless of tyre configuration or settings), soil strength increased to the full measured depth (600 mm), but relative changes before vs. after traffic became progressively smaller with increased soil depth. The power loss in rolling resistance was consistently greater with the heavier tractor, and rut depth was directly related to tyre inflation pressure. Full article

With the aggravation of the energy crisis and environmental problems, the new energy electric vehicle industry has ushered in vigorous development. However, with the continuous increase in car ownership, traffic accidents and other issues have gradually attracted widespread attention. Some existing stability coordination control systems often have problems, such as single stability judgment method and strong coupling between different subsystems. Therefore, based on previous research, it is necessary to further optimize the method of judging the vehicle’s stability state, establish clear coordination rules, and reasonably solve the coupling problem between subsystems. This is of great significance for promoting the further development of the electric vehicle industry. Due to four-wheel-distributed driving and four-wheel-distributed steering electric vehicles having the characteristics of integrated driving, flexible steering, and easy fault-tolerant control, it has unique advantages in improving vehicle stability and is a good carrier for designing and constructing the stability coordination control system. In this paper, four-wheel-distributed driving and four-wheel-distributed steering (4WD-4WS) electric vehicles are taken as the research object, and a coordinated control strategy of four-wheel steering and four-wheel drive is proposed. Firstly, in order to realize the accurate judgment of vehicle stability, based on the vehicle two-degree-of-freedom two-track model and magic tire model, this paper uses the phase plane law to divide the phase plane stability region of the vehicle and introduces the stability quantification index PPS-region for the evaluation of vehicle stability. Secondly, a fuzzy variable parameter active rear-wheel steering controller and a compensated yaw moment controller are designed. Then, for the coupling problem between the two controllers, a coordination rule is proposed based on the stability index PPS-region of the phase plane stability region. Finally, a hardware-in-the-loop testbed is built to verify the feasibility of the coordination control strategy proposed in this paper. Experimental results show that: When the vehicle is in different stable states, according to the divided steady state, the control strategy can be correctly switched to the corresponding control strategy, and the work of each subsystem can be reasonably coordinated. Under the continuous gain sine condition, the control algorithm can reduce the maximum amplitude of the yaw rate error response curve by 73% and the side slip angle error response curve by 85%. Compared with a single stability control system, the coordinated stability control algorithm can improve the control effect of yaw rate and side slip angle by 20% and 62.5%. In the case of double lane-change, the control algorithm can reduce the maximum amplitude of the yaw rate error response curve by 68.5% and the side slip angle error response curve by 57.4%. Compared with a single stability control system, the coordinated stability control algorithm can improve the control effect of yaw rate and side slip angle by 40.6% and 44.7%. Full article

To address the problem in which wheel longitudinal slip rate directly affects the dynamics and handling stability of a vehicle under driving conditions, front and rear dual-motor four-wheel drive electric vehicles (4WD EVs) were selected as the research object in this study. An acceleration slip regulation (ASR) control strategy based on nonlinear model predictive control (NMPC) is proposed. First, the vehicle dynamics model and the Simulink/CarSim co-simulation platform were built. Second, an ASR controller with intervention and exit mechanisms was designed with the control objective of tracking reference speed or optimal slip rate. Then, considering the problem that the left and right wheels could not freely distribute torque under the condition of a split road surface, the motor output torque was determined in accordance with the wheel with the larger slip rate to enhance passibility. Finally, on the basis of the built Simulink/CarSim co-simulation platform, slip rate control simulation experiments were performed on a snow-covered road, a wet asphalt road, a docking road, and a split road. The designed controller can better track target slip rate and it exhibits better dynamic performance and stability than the method with PID control under different road conditions, especially under low speed and low adhesion road conditions, and its robustness can also meet the requirements. Full article

In the field of new energy vehicles, 4WD PHEVs show strong energy-saving potential. A single energy management strategy, nevertheless, has difficulty achieving the energy-saving potential due to the complex, nonlinear energy system of the 4WD PHEV. To cope with it, a hierarchical energy management strategy (H-EMS) for 4WD PHEVs is proposed in this paper to achieve energy management optimization. Firstly, the future speed information is predicted by the speed prediction method, and the upper energy management strategy adopts the model predictive control (MPC) based on the future speed information to carry out the power source distribution between the engine and the battery. Secondly, the lower energy management strategy performs the power component distribution of the front motor and the rear motor based on an equivalent consumption minimization strategy (ECMS). Finally, the simulation based on MATLAB/Simulink is performed, validating that the proposed method has more energy-saving capabilities, and the economy is improved by 11.87% compared with the rule-based (RB) energy management strategies. Full article

Energy management strategies are vitally important to give full play to energy-saving four-wheel-drive plug-in hybrid electric vehicles (4WD PHEV). This paper proposes a novel dual-adaptive equivalent consumption minimization strategy (DA-ECMS) for the complex multi-energy system in the 4WD PHEV. In this strategy, management of the multi-energy system is optimized by introducing the categories of future driving conditions to adjust the equivalent factors and improving the adaptability and economy of driving conditions. Firstly, a self-organizing neural network (SOM) and grey wolf optimizer (GWO) are adopted to classify the driving condition categories and optimize the multi-dimensional equivalent factors offline. Secondly, SOM is adopted to identify driving condition categories and the multi-dimensional equivalent factors are matched. Finally, the DA-ECMS completes the multi-energy optimization management of the front axle multi-energy sources and the electric driving system and releases the energy-saving potential of the 4WD PHEV. Simulation results show that, compared with the rule-based strategy, the economy in the DA-ECMS is improved by 13.31%. Full article

The market for electric vehicles is growing rapidly. Among them, the demand for a dual motor type 4 WD (Four -Wheel Driving) system is increasing. In this paper, we present the Torque Matching Strategy (TMS) method to select the optimal torque distribution ratio for dual motors. The TMS controller operates to set the optimal efficiency point by linearizing the drive efficiency combination of the two motors. Driving simulation and testing were performed through five drive cycles in the driver model interworking environment implemented in MATLAB and Carsim. The optimal distribution ratio was derived according to the front and rear gear ratios under the load condition, and the driving was verified by comparing it with the TMS control method. The efficiency was numerically verified by comparing the power loss of the driving motor. It reduced up to 34% in Urban Dynamometer Driving Schedule and up to 56.3% in Highway fuel efficiency test. The effectiveness of the TMS control method was demonstrated through the distribution rate trend based on the operation cycle and power loss. Full article

In response to the poor adaptability of existing harvesters to complex operating conditions in the field, this study took a three-row four-wheel-drive (4WD) corn harvester as the research object, designed a traveling transmission system layout, proposed a control strategy of driving torque distribution, simulated, and analyzed each of the four states of harvester drive wheels slippage. The results showed that under the driving wheels slipping condition, after applying torque control, the adjustment time was 43.3% shorter than that without control in the case of single wheel slipping, 11.1% shorter than that without control in the case of two wheels slipping on the same axle, 41.4% shorter than that without control in the case of two wheels slipping on different axles, and 36.6% shorter than that without control in the case of three driving wheels slipping. The application of drive torque distribution control could significantly improve the traction and passing ability of the corn harvesters during operation, as well as made the harvester travel more smoothly, thus improving the harvest quality. The drive torque distribution control can be applied not only to the three-row corn harvester, but also to other types of harvesters, and self-propelled agricultural machinery to enhance their adaptability, improving their operation quality. It has a significant reference value for the development of the driving system on walking agricultural machinery. Full article

To determine the effect of the tractor driving system type on the soil compaction and soil behavior a series of tests was conducted using Goldoni 240 tractor with a power rate of 30.8 kW and included four similar tires at three different driving systems (4WD, rear-wheel drive (RWD) and front-wheel drive (FWD)). To evaluate these systems’ effects on soil compaction, tests were conducted at three soil moisture contents (10, 15 and 20% d.b.), three tire inflation pressures (170, 200 and 230 kPa), and three tractor speeds (1.26, 3.96 and 6.78 km/h). Soil bulk density was measured at three average depths of 20, 30 and 40 cm. To evaluate soil compaction, cylindrical cores were used and to assess soil behavior during this process, the soil displacement in a three coordinate system was measured using three displacement transducers. It was found that the 4WD system created the least bulk density of 1155 kg/m³, while the FWD system led to the highest density of 1241 kg/m³. Maximum vertical soil compression of 55 mm occurred for the FWD system and it declined to 43 and 36 mm in RWD and 4WD systems, respectively. Soil displacement in the horizontal and lateral directions was larger for the FWD system in comparison to the other systems. With increment of speed and depth soil compaction decreased. Minimum bulk density of 1109 kg/m³ was occurred at velocity of 6.78 Km/h using the 4WD system, also with this system at the depth 40 cm density was 1127 kg/m³. While at velocity of 1.26 Km/h and depth of 20 cm soil density was 1190 kg/m³. Full article

Since the introduction of four-wheel drive (4WD) and especially front wheel assist (FWA), many studies have been conducted on the optimal weight distribution between tractor front and rear axles because this influences traction efficiency. The aim of this paper is to evaluate the traction and efficiency advantages in the adoption of mechanical ballast position adjustment devices. The tested device is an extendable ballast holder mounted on the front three-point hitch of the tractor, able to displace the ballast up to 1 m away from its original position. An estimation of the fuel consumption during ploughing with the extendable ballast holder in different configurations was performed. Tractive performance was evaluated through drawbar tests, performed on loam soil with a 4WD tractor having a maximum engine power of 191 kW and a ballasted mass of 9590 kg. Results show that changing the tractor weight distribution over the range allowed by the extendable ballast holder produces limited effects in terms of tractive performance and fuel saving. The adoption of such devices is thus ineffective if other fundamental factors such as tyre pressure, choice of the front-to-rear wheel combination and lead of the front wheels are not considered during tractor setup. Full article