Experimental Technology and Management

[Objective] Vehicle suspension systems are pivotal to the comfort, handling stability, and safety. Traditional passive suspensions are limited by fixed parameters that cannot adapt to varying road excitation, while fully active solutions remain prohibitively expensive and energy-intensive for mass-market adoption. Magnetorheological(MR) semi-active suspension systems offer a promising compromise because they can vary the damping force almost instantaneously with minimal power consumption. Despite a rich body of simulation studies, vehicle engineering education still lacks a low-cost, open-architecture experimental virtual instrumentation platform that exposes students to the entire “modeling–control–validation” workflow. This paper presents the design, implementation, and pedagogical deployment of an innovative quarter-car test bench that integrates measurement and control technology, embedded computing, and reproducible laboratory exercises. [Methods] The platform is based on a two-degree-of-freedom quarter-car rig consisting of sprung and unsprung masses connected by a coil spring, a tire-equivalent spring, and a commercially available MR damper whose force is continuously adjustable with currents ranging from 0 A to 1.5 A. A high-precision servo-electric cylinder generates vertical displacements that replicate random road profiles synthesized by a filtered-white-noise algorithm; profile severity is scaled to standard road classes A–D. Multi-modal sensing is achieved using IEPE accelerometers, magnetostrictive displacement transducers, and strain-gauge force sensors whose outputs are synchronously sampled at 1 kHz by a hybrid data-acquisition architecture that combines NI 9230 and ART USB-313 XA cards. A dual-core “STM32-LabVIEW” control backbone partitions tasks: an STM32H7 microcontroller executes real-time damping control algorithms at 1 kHz, while a LabVIEW host application provides supervisory control, data logging, and a graphical user interface. A hierarchical “three-layer” coupling(physical–algorithm–execution) and a “dual-loop” structure(outer excitation–response loop and inner damping-force loop) are introduced to guarantee microsecond-level synchronization and millisecond-level control latency. To support educational objectives, the system exposes all signals through open APIs. This allows students to implement and compare classical skyhook, groundhook, and hybrid skyhook–groundhook policies in MATLAB/Simulink before validating them on the rig. [Results] Extensive experimental campaigns demonstrated the component-level and system-level performances of the proposed test bench. At the component level, steady-state sinusoidal tests revealed that the MR damper force increased monotonically with applied current, rising from 60 N at 0 A to 220 N at 1.5 A, with a clear saturation trend beyond 1.2 A. This characteristic was well captured by an embedded hyperbolic–tangent model that was updated online to compensate for temperature drift. At the system level, C-class random-road experiments conducted at 36 km·h^–1 showed that the hybrid skyhook–groundhook algorithm suppressed sprung-mass vertical acceleration, suspension deflection, and tire dynamic load remarkably better than the passive setup, although the exact percentage improvements are not reported herein. The results of five-run repeatability tests showed that the coefficient of variation was less than 5% for all key metrics, confirming the robustness of the test bench. Comparative tests across B-, C-, and D-class roads at 72 km·h^–1 further demonstrated that despite intensified vehicle vibration on harsher road profiles, the semi-active controller consistently outperformed the passive configuration in mitigating these responses. Student feedback collected over two academic semesters implied that the “theory–simulation– experiment” workflow shortened the concept-to-validation cycle and significantly improved engagement. [Conclusions] The proposed magnetorheological semi-active suspension platform successfully bridges the gap between theoretical studies and hands-on experimentation. Its modular hardware and open-source virtual instrumentation platform make it affordable and extensible to other vehicle engineering topics. In addition, the embedded measurement and control framework equips students with industry-relevant skills. Future work will integrate energy-harvesting shock absorbers and cloud-based teleoperation to transform the rig into a cyber–physical learning factory.