Search Results (480)

With the rapid advancement of intelligent technologies in electric vehicles, various control technologies and algorithms are emerging. Most existing research, however, is limited to simulations of single modules such as suspension, braking, and battery management, lacking comprehensive modeling and simulation for the entire vehicle system, which impedes the integrated development and verification of advanced intelligent technologies. Therefore, this article focuses on the vehicle control system of electric vehicles. It first analyzes the overall scheme and clarifies the core functions of system operation control, fault detection, and storage. Subsequently, a data acquisition simulation platform for the vehicle control system is established based on MATLAB/Simulink, creating simulation modules for accelerator pedal, braking pedal, key position, and gear signal, forming a complete vehicle simulation platform. For the established simulation platform, specific electric vehicle model parameters are set, and under the QC/T759 urban driving conditions, simulations of the electric vehicle’s operation are conducted to obtain relevant signals such as vehicle speed, accelerator pedal, and braking pedal, verifying the feasibility of the vehicle control system. Finally, a hardware platform for the entire vehicle power system is built, and based on the PCAN-Explorer5 software, the connection and debugging of the vehicle controller, battery management system, and motor control unit are achieved to obtain the status parameters of each system and debug the vehicle control system, laying the foundation for the actual operation of the pure electric SUV. Through the simulation of the electric vehicle’s control system, the R&D cycle is greatly shortened, development costs are reduced, and a foundation is established for the actual vehicle debugging of electric vehicles. Full article

Considering the variability of driving conditions in mining areas, existing control strategies are difficult to meet the comprehensive performance requirements of mining dump trucks in the longitudinal, lateral, and vertical directions. Longitudinal, lateral, and vertical (LLV) coordinated control of active hydro-pneumatic suspension system based on model predictive control (MPC) is constructed in this paper. The vehicle dynamic response under random road surface input based on wheelbase characteristics is established, and the rationality of the active hydro-pneumatic suspension LLV coordinated control strategy based on MPC is analyzed. Handling stability is taken as the overall control objective for active hydro-pneumatic suspension on C-class road surfaces. The dynamic tire loads of the six wheels of the mining dump truck are reduced by 25.8%, 29.1%, 30.6%, 27.6%, 29.9%, and 28.1%, respectively, in the unloaded state, while the longitudinal, lateral, and vertical body accelerations have not deteriorated. Under the E-class road surface, the overall control objective of the mining dump truck is comfort, and the longitudinal, lateral, and vertical accelerations in the unloaded state have been optimized by 34.6%, 31.4%, and 34.1%, respectively. Full article

The development of modern vehicles faces an increase in complexity, as well as a need for shorter development cycles and a seamless cross-domain integration. In order to meet these challenges, a graph-based design language which formalizes and automates engineering workflows is presented and applied in a design case study to a Formula Student race car suspension system. The proposed method uses an ontology-based vocabulary definition and executable model transformations to compile design knowledge into a central and consistent design graph. This graph enables the automatic generation of consistent 3D CAD models, domain-specific simulations and suspension kinematic analyses, replacing manual and error-prone tool and data handover processes. The design language captures both the structural and dynamic behavior of the suspension, supports variant exploration and allows for integrated validation, such as 3D collision detection. The study illustrates how graph-based design languages can serve as ‘digital DNA’ for knowledge-based product development, offering a scalable, reusable platform for engineering automation. This approach enhances the digital consistency of data, the digital continuity of processes and the digital interoperability of tools across all relevant engineering disciplines in order to support the validation of early-stage designs and the optimization of complex systems. Full article

The increasing demand for food is the driving force behind the search for novel, more selective, and less hazardous agrochemicals. Natural products are gaining prominence recently due to the promise of being green agrochemicals, but many natural products are poorly soluble in water, which reduces their applicability. In this work, we successfully formulated a water-insoluble Saussurea lappa root extract into a stable aqueous suspension using xanthan gum. The colloidal suspension was characterized by rheology, dynamic light scattering, and zeta potential. The results demonstrated that the suspension is a stable, sprayable, shear-thinning viscoelastic system (weak gel). A series of S. lappa solutions with xanthan gum were prepared and tested against five plant species, observing the inhibitory effect on the shoots and roots. The results were also compared with the commercial herbicide Dual. The S. lappa extract presented results comparable to or even greater than Dual for Lactuca sativa, Cucumis sativus, Brachiaria decumbens, and Bidens pilosa. However, it showed low inhibitory activity for Sorghum bicolor, highlighting its potential for selective weed control. This work illustrates xanthan gum as an effective vehicle for formulating insoluble natural products and demonstrates that S. lappa extract is a promising candidate for developing novel herbicides. Full article

This paper presents a virtual reference-based preview semi-active suspension system using a Magneto-Rheological (MR) damper to improve ride comfort when traversing bumps. The algorithm is designed to track the virtual reference profile of the vehicle’s corner by introducing a Model Predictive Control (MPC) method while considering the passivity of the MR damper. The proposed MPC is formulated to rely solely on estimable variables from an Inertial Measurement Unit (IMU) and vertical accelerometer. To support implementation on an Electronic Control Unit (ECU), the suspension state estimator employs a simple band-limited filtering structure. The proposed method is evaluated in simulation and achieves performance comparable to a controller that has accurate prior knowledge of the road profile. In addition, simulation results demonstrate that the proposed approach exhibits low sensitivity to sensor noise and bump perception uncertainty, making it well suited for real-world vehicle applications. Full article

Pine wilt disease (PWD), caused by Bursaphelenchus xylophilus, is driven by a tri-component system involving the pinewood nematode, Monochamus spp. beetle vectors, and susceptible pine hosts. Chemical control remains a scenario-dependent option for emergency suppression and high-value protection, but its deployment is constrained by strong regional regulatory and practical differences. In Europe (e.g., Portugal and Spain), field chemical control is generally not practiced; post-harvest phytosanitary treatments for wood and wood packaging rely mainly on heat treatment, and among ISPMs only sulfuryl fluoride is listed for wood treatment with limited use. This review focuses on recent progress in PWD chemical control, summarizing advances in nematicide discovery and modes of action, greener formulations and delivery technologies, and evidence-based, scenario-oriented applications (standing-tree protection, vector suppression, and infested-wood/inoculum management). Recent studies highlight accelerated development of target-oriented nematicides acting on key pathways such as neural transmission and mitochondrial energy metabolism, with structure–activity relationship (SAR) efforts enabling lead optimization. Formulation innovations (water-based and low-solvent products, microemulsions and suspensions) improve stability and operational safety, while controlled-release delivery systems (e.g., micro/nanocapsules) enhance penetration and persistence. Application technologies such as trunk injection, aerial/Unmanned aerial vehicle (UAV) operations, and fumigation/treatment approaches further strengthen scenario compatibility and operational efficiency. Future research should prioritize robust target–mechanism evidence, resistance risk management and rotation strategies, greener formulations with smart delivery, and scenario-based exposure and compliance evaluation to support precise, green, and sustainable integrated control together with biological and other sustainable approaches. Full article

Vehicle repeated passes over soft terrain alter the soil’s bearing and shear behavior, thereby affecting vehicle mobility and energy consumption. To address this issue, this study conducted cyclic compression and shear tests on beach sand with moisture contents of 5%, 15%, and 25%. A constitutive model incorporating the coupling effects of loading cycles (N) and moisture content (ω) was developed based on the Bekker and Janosi model framework. The model expresses compression parameters as functions of N and ω, and describes shear behavior through the strength evolution function k(N,ω) and deformation modulus function h(N,ω). Results show excellent agreement between the model predictions and experimental data (R² > 0.92). Furthermore, a vehicle–soil coupled dynamics model was established based on the proposed constitutive model, forming a comprehensive analytical framework that integrates soil meso-mechanics with full vehicle–terrain interaction. This work provides valuable theoretical and technical support for predicting vehicle trafficability on coastal soft soils and optimizing vehicle suspension systems. Full article

Improving the ride comfort of commercial vehicles is crucial for driver health and operational safety. This study focuses on optimizing the parameters of a cab suspension system to improve its vibration isolation performance. Initially, nonlinear fitting was applied to experimental data characterizing air spring stiffness and damping, which informed the development of a multi-body rigid-flexible coupled dynamic model of the suspension system; its dynamic characteristics were subsequently validated through modal analysis. Road excitation data, filtered through the chassis suspension, were collected during vehicle testing, and displacement excitations for ride comfort simulation were reconstructed using virtual iteration technology. Thereafter, an integrated ISIGHT platform, combining ADAMS and MATLAB, was employed to systematically optimize suspension parameters and key bushing stiffness via a multi-island genetic algorithm. The optimization results demonstrated significant performance improvements: on General roads, the overall weighted root-mean-square acceleration was markedly reduced with enhanced isolation efficiency; on Belgian pave roads, resonance in the cab’s X-axis direction was effectively suppressed; and on Cobblestone roads, the pitch angle was successfully constrained within the design limit. This research provides an effective parameter matching methodology for performance optimization of cab suspension systems. Full article

Active suspension systems can significantly enhance vehicle ride comfort and attitude stability, but often at the cost of increased energy consumption. To achieve both high dynamic performance and reduced energy usage, this study proposes an eigenstructure-oriented optimization method for active suspensions. Controller design is reformulated as a synergistic process of modal regulation and dynamic response optimization, in which partial eigenstructure assignment redistributes the dominant modes and system responses are computed using fourth-order Runge–Kutta integration. An energy-minimization optimization problem with performance constraints is then solved via the sequential quadratic programming (SQP) algorithm. Simulation results show that the proposed method markedly improves vibration performance: peak body acceleration is reduced from 3.48 m/s² to 1.70 m/s² (a 51.1% reduction), and the root mean square (RMS) acceleration decreases from 0.74 to 0.40 (a 45.6% reduction), while body displacement is also significantly suppressed. Compared with passive suspension and proportional–integral–derivative (PID) active suspension, the proposed system achieves superior performance in key indices such as body acceleration and displacement, leading to noticeably improved ride comfort and attitude stability. Furthermore, robustness analysis indicates that the method remains effective under variations in the receptance matrix, with only minor influence on system performance, demonstrating the practical applicability of the proposed control strategy. Full article

The operational efficiency and precision of boom sprayers, as critical equipment for protecting field crops, are vital to global food security and agricultural sustainability. In precision agriculture systems, achieving uniform pesticide application fundamentally depends on maintaining stable boom posture during operation. However, severe boom vibration not only directly causes issues like missed spraying, double spraying, and pesticide drift but also represents a critical bottleneck constraining its functional realization in cutting-edge applications. Despite its importance, achieving absolute boom stability is a complex task. Its suspension system design faces a fundamental technical contradiction: effectively isolating high-frequency vehicle vibrations caused by ground surfaces while precisely following large-scale, low-frequency slope variations in the field. This paper systematically traces the evolutionary path of self-balancing boom technology in addressing this core contradiction. First, the paper conducts a dynamic analysis of the root causes of boom instability and the mechanism of its detrimental physical effects on spray quality. This serves as a foundation for the subsequent discussion on technical approaches for boom support and balancing systems. The paper also delves into the evolution of sensing technology, from “single-point height measurement” to “point cloud morphology perception,” and provides a detailed analysis of control strategies from classical PID to modern robust control and artificial intelligence methods. Furthermore, this paper explores the deep integration of this technology with precision agriculture applications, such as variable rate application and autonomous navigation. In conclusion, the paper summarizes the main challenges facing current technology and outlines future development trends, aiming to provide a comprehensive reference for research and development in this field. Full article

Three-wheeled vehicles are gaining popularity in European and Asian cities due to their low cost, stability, maneuverability, and compact size. Among these, tilting vehicles facilitate cornering, maintain stability, and reduce centrifugal forces. This study investigates a delta-configured, three-wheeled tilting vehicle designed for people with reduced mobility. Vehicle dynamics were analyzed using ADAMS/Car simulations, including steady-state cornering and single-lane change tests, focusing on body motion and forces in suspension and steering systems. Results show that tilting of the body significantly enhances cornering safety compared to non-tilting three-wheelers, providing insights for designing efficient urban vehicles for diverse user groups. Full article

System time delays and nonlinear unmodeled dynamics severely constrain the control performance of the Active Suspension Electro-Hydraulic Servo Actuator (ASEHSA). To tackle these challenges, this paper presents a Dynamic Error Differentiation-based Model-Free Adaptive Control (DE-MFAC) strategy integrated with an Improved Particle Swarm Optimization (IPSO) algorithm. Established under the Model-Free Adaptive Control (MFAC) framework, the DE-MFAC integrates a dynamic error differentiation mechanism and an implicit expression of time delays, thus removing the dependence on a precise system model. The traditional PSO algorithm is improved by incorporating an inertia weight adjustment strategy and a boundary reflection wall strategy, which effectively mitigates the issues of local optima and boundary stagnation. In AMESim 2021, a 1/4 vehicle active suspension electro-hydraulic actuation system model is constructed. To ensure an impartial evaluation of controller performance, the IPSO algorithm is employed to optimize the parameters of the PID, MFAC, and DE-MFAC controllers, respectively. Co-simulations with Simulink 2023b are conducted under two time delay scenarios using a composite square-sine wave signal as the reference. The results indicate that all three IPSO-optimized controllers realize effective position tracking. Among them, the DE-MFAC controller exhibits the optimal performance, demonstrating remarkable advantages in reducing tracking errors and balancing settling time with overshoot. These findings verify the effectiveness of the proposed control strategy, time delay compensation mechanism, and optimization algorithm. Future research will involve validation on a physical ASEHSA platform, further exploration of the method’s applicability and robustness under diverse operating conditions, and extension to other industrial systems with similar nonlinear time delay features. Full article

This study quantitatively evaluated the performance of a semi-active electronically controlled suspension (ECS) on low-friction (low-μ) road surfaces. A mid-size passenger vehicle equipped with a reverse-type continuously variable damper was tested through double lane change (DLC) maneuvers on the snow-covered Arjeplog test track in Sweden. The proposed semi-active control logic, based on Skyhook control, was designed to enhance handling stability by integrating roll rate control with yaw moment compensation control using roll moment distribution. Under semi-active only operation, the peak yaw-rate amplitude decreased by approximately 16% compared with the conventional fixed-damping mode, confirming a clear improvement in yaw stability. Furthermore, when the ECS operated in conjunction with the vehicle dynamic control (VDC) system through a lateral-acceleration signal linkage, the vehicle exhibited smoother roll and yaw responses, as well as highly repeatable steering behavior, across multiple tests. These results demonstrate that the proposed semi-active ECS not only improves transient yaw stability but also enhances response consistency when combined with VDC, providing a practical foundation for integrated chassis control development under real-world low-µ conditions, such as snow and wet roads. Full article

Dynamic loads on a vehicle’s running gear generated when driving over uneven roads or surfaces have a destructive effect on its components and, consequently, on the vehicle’s reliability. Special vehicles, especially off-road vehicles, are operated differently from traditional vehicles. Deformable surfaces can induce significant dynamic loads on vehicle running gear components even at low speeds, significantly limiting safe driving speeds. This article presents experimental vehicle tests conducted on four test track sections at three predefined vehicle speeds (10, 20, and 30 km/h). The experimental results demonstrate a clear dependence of dynamic loads on the off-road vehicle’s speed on dirt surfaces. Differences were observed between the measurement sections, suggesting that standard road profile metrics (e.g., RMS (Root Mean Square) profile height change) do not fully predict actual loads, requiring continuous monitoring of vehicle operating conditions. Compared to paved roads, where loads are more predictable, ground surfaces generate unique vibration patterns even at low driving speeds. RMS values for the measurement sections ranged from 0.02 to 0.06 m. Therefore, it is necessary to adapt test methods to specific ground conditions, with driving speed as a key research parameter. Full article

To address issues such as chassis attitude deviation, reduced operational efficiency, and diminished precision when agricultural machinery operates in complex terrains—including steep slopes and fragmented plots in hilly and mountainous regions—a servo electric cylinder-based active suspension levelling system has been designed. Real-time dynamic control is achieved through a fuzzy PID algorithm. Firstly, the suspension’s mechanical structure and key parameters were determined, employing a ‘servo electric cylinder-spring-shock absorber series’ configuration to achieve load support and passive vibration damping. Secondly, a kinematic and dynamic model of the quarter-link suspension was established. Finally, Simulink simulations were conducted to model the agricultural machinery traversing mountainous, uneven terrain at segmented stable operating speeds, thereby validating the suspension’s control performance. Simulation results demonstrate that the system maintains chassis height error within ±0.05 m, chassis height change rate within ±0.2 m/s, and response time ≤ 0.8 s. It rapidly and effectively counteracts terrain disturbances, achieving precise chassis height control. This provides theoretical support for designing whole-vehicle levelling systems for small agricultural machinery in hilly and mountainous terrains. Full article