No abstract

The transient magnetorheological response of magnetorheological elastomer (MRE) is critical to the control system in its applications. Overlong magnetorheological response time will prolong the control time delay of whole application system, which will lead to the degradation of control accuracy and timeliness, or even bring unwanted results. Therefore, it is particularly important to improve the transient magnetorheological response property of MRE for enhancing control efficiency of system. To this end, this paper synthesized a kind of new magnetic filler particle, carbonyl iron powder (CIP)@FeNi, which possesses Fe–Ni nano-flakes on its surface. Vibrating sample magnetometer test results showed that CIP@FeNi possessed superior magnetization under low magnetic field when compared with CIP. By partially replacement of CIP with CIP@FeNi, new dimorphic MREs were prepared. The influence of CIP@FeNi content on both of the transient magnetorheological response and magnetorheological mechanical properties of MRE were experimentally studied. Results indicated that CIP@FeNi is efficacious for improving the response velocity of MRE. In the rise edge, characteristic response time shows obvious decrease trend with increasing content of CIP@FeNi. In addition, at CIP@FeNi content of 2 vol% and 4 vol%, the doped CIP@FeNi can also enhance the magnetorheological property of MRE. This study provides a novel and effective way to improve the transient magnetorheological response property of MRE, which is of great significance for improving the control efficiency of MRE devices.

In the intelligent control system of magnetorheological (MR) suspension of all-terrain vehicle(ATV), the low-frequency disturbance(LFD) in the measured feedback signal (acceleration) makes the controller unable to calculate the theoretical control force accurately. Especially, when the frequency of the LFD signal is close to that of the actual acceleration signal, the LFD can’t be filtered by designing a traditional filter. Based on the above questions, this paper proposes an incremental proportion integration differentiation (IPID) strategy to address the issue of LFD in the measured feedback acceleration signal of the MR suspension system of ATV. First of all, the model of 1/4 vehicle suspension in consideration of LFD is established, the source of LFD is analyzed which is due to the transformation of Coriolis acceleration under the condition of vehicle body pitch and roll. Next, a semi-active IPID controller is designed by utilizing differential derivation of discrete PID and semi-active principle to eliminate the LFD component mixed in the acceleration signal by making a difference. The particle swarm optimization (PSO) algorithm is utilized to optimize the parameters of the controller, which is then verified through numerical simulation. Subsequently, a real vehicle control experiment is carried out based on a 4x4 ATV equipped with the MR suspension system and implemented by DSP controller with the designed IPID algorithm. The effectiveness of the prosed method is evaluated under the speed 10km/h and E road. And the designed method is compared with the traditional PID control algorithm through simulation and experimentation to demonstrate the superiority and rationality of "filtering out" LFD signal and improving control effectiveness.

Magnetorheological dampers (MRD) are increasingly used in smart structural damping systems due to their good damping properties. In practical applications, as a nonlinear device, the parameters of the internal excitation coil of the magnetorheological damper will change during operation under the influence of the temperature and external environment, deteriorating the dynamic performance of the output current of the driver and reducing the damping effect of the system. Therefore, the current driver needs to be optimized for this phenomenon in order to ensure accurate current output. In this paper, a mathematical model of the buck circuit combined with the MRD equivalent circuit is established, and after analyzing the model, the parameters of the PI controller are rectified to lay the foundation for the design of the adaptive law. Then, with the help of the fuzzy control method, a fuzzy PI control strategy for MRD current driver is established, which enables the current driving system to adjust the control parameters adaptively when the MRD parameters change and ensure the accurate driving current output. The experimental results demonstrate that the fuzzy PI control strategy has a stronger robustness in the face of parameter changes of the control object compared with the traditional PI control at a system parameter change rate of 40%.