The loading system of a vehicle rolling test machine is the core module for achieving precise dynamic force control. Its design requires coordinated optimization of mechanical structure, control algorithms, and sensor feedback. This system simulates the real force environment of a vehicle during driving, providing adjustable dynamic loads to the tested components (such as the powertrain and transmission system). The control accuracy directly affects the reliability of the test results. Its core mechanism can be broken down into four dimensions: mechanical actuation, dynamic compensation, closed-loop feedback, and software algorithms.
The mechanical actuator is the basic carrier of dynamic force loading. The loading device of a vehicle rolling test machine typically uses hydraulic, electric, or mechanical transmission methods, with hydraulic loading being widely used due to its fast response speed and high output torque. For example, some test benches use a hydraulic double-acting cylinder to push a steel ball against a pressure block, and then the force is transmitted to the drive shaft via a lever retainer, ultimately acting between the upper and lower test rings. This design utilizes the reciprocating motion characteristics of the hydraulic cylinder, combined with the lever principle, to amplify and transmit force. Simultaneously, the point contact between the steel ball and the pressure block reduces friction loss and improves energy transfer efficiency.
Dynamic compensation technology is used to compensate for inherent system delays and external interference. When a vehicle suddenly brakes from a constant speed, the loading system needs to respond quickly to simulate the combined effect of inertial force and braking force. In this situation, feedforward control can adjust the output in advance based on anticipated load changes, shortening the response time; while the disturbance observer estimates external disturbances (such as power grid fluctuations and mechanical vibrations) and generates compensation signals, improving the system's anti-interference capability. Furthermore, elastic deformation of the mechanical structure may introduce hysteresis, requiring stiffness optimization or structural compensation design to reduce its impact.
A closed-loop feedback mechanism is key to achieving precise dynamic force control. High-precision sensors (such as torque sensors and displacement sensors) collect loading force and platform state parameters in real time, converting physical signals into electrical signals and transmitting them to the control system. The control system dynamically adjusts the actuator output by comparing the deviation between the actual and target values. For example, when the loading force exceeds the set value, the system can automatically reduce the hydraulic cylinder pressure or adjust the motor speed, forming a closed-loop cycle of "measurement-comparison-correction." Some vehicle rolling test machines also integrate pressure and displacement sensors to achieve dual monitoring of loading force and platform lifting height, ensuring safety boundaries.
At the software algorithm level, test benches are typically equipped with dedicated control software, integrating multiple control modes (such as constant torque, constant speed, and ramp loading) and advanced algorithms. Model predictive control (MPC) can predict future load changes based on vehicle dynamics models and adjust control variables in advance; fuzzy control handles uncertainties through linguistic variables, enhancing system robustness. Some systems also support open interfaces, allowing users to embed custom algorithms or connect to third-party simulation platforms (such as MATLAB/Simulink) to achieve virtual-real co-simulation and expand the scope of test scenarios.
The response speed and accuracy of the actuators directly affect the control effect. Hydraulic actuators control oil flow through servo valves, generating high-frequency reciprocating forces, often used to simulate vibration loads caused by road surface unevenness; electric loading methods (such as AC dynamometers) absorb energy by adjusting motor frequency and torque, with response times typically in the millisecond range, meeting the requirements of dynamic load simulation. The selection of actuators must comprehensively consider bandwidth, resolution, and load capacity to ensure matching with the control strategy.
The complexity of dynamic load simulation is also reflected in the handling of nonlinear factors. For example, during vehicle acceleration, the coefficient of friction between the tire and the roller changes with speed; during braking, thermal deformation of the material may lead to a redistribution of contact stress. To address these challenges, some test benches employ adaptive control, optimizing control performance by adjusting parameters in real time; or they introduce machine learning algorithms to predict system behavior based on historical data, further improving dynamic response accuracy.
The loading system of the vehicle rolling test machine achieves precise control of dynamic forces through a deep integration of mechanical execution, dynamic compensation, closed-loop feedback, and software algorithms. This process not only relies on high-precision hardware design but also requires real-time analysis and optimization of complex working conditions by software algorithms, ultimately providing vehicle development with test data that closely approximates real-world scenarios and shortening product iteration cycles.
