Design And Optimization Of A Suspension Meandering Magnetic Circuit Magnetorheological Damper

With the rapid development of automobile technology,people have put forward higher requirements for ride comfort and handling stability during the driving process.Traditional passive dampers cannot adjust damping and are difficult to meet the requirements of ride comfort under different working conditions.Magnetorheological dampers can achieve infinite control of damping by adjusting the external magnetic field,which can effectively improve ride comfort and handling stability of automobiles.However,the existing traditional valve-type magnetorheological dampers have small damping force at low speeds,so they cannot effectively resist vehicle roll and limit the improvement of driving performance.In order to solve this problem,this paper proposes a magnetorheological damper(MR Damper)with a meandering magnetic circuit,which can produce large damping force even at low speeds,and can simultaneously meet the requirements of suppressing roll and reducing vibration under normal working conditions.The main work is as follows:(1)Based on the industry standard QC/T491-2018 "Performance Requirements and Test Methods for Automotive Shock Absorbers",a magneto-rheological damper with a meandering magnetic circuit was designed for a common SUV passenger vehicle,so that it has a large damping force at low speed to meet the requirement of anti-roll.The overall structure of the damper was designed,and the strength verification of relevant components was carried out,and finally,the magnetic circuit was designed and calculated.(2)A mechanical model for the damping force of a magnetorheological damper with a working mode of shear flow was constructed.The pressure drop and flow rate were calculated for the working gap and through-hole of the magnetorheological damper,respectively.Finally,the damping force model for the magnetorheological damper with a meandering magnetic circuit was derived.For comparison purposes,the damping force model for the traditional magnetic circuit was also derived.(3)Conduct magnetic field design and electromagnetic finite element analysis on the control valve of the magnetorheological damper.Based on the structural factors that affect the magnetic induction intensity in the working clearance area of the damper,finite element simulations were performed on individual structural dimensions to optimize the control valve’s groove height,groove depth,and gap thickness in order to achieve the magnetic induction intensity goal in the working clearance area.Finally,the output characteristics of the damper were simulated,and the relationship curve between damping force and velocity under different currents was obtained and compared with the traditional magnetic circuit magnetorheological damper.(4)Using a design of experiments(DOE)approach,sensitivity analysis was conducted on the main structural parameters that affect the magnetic induction intensity in the working gap.The parameters that require optimization were identified.A Taguchi design of experiments table was created by dividing the different factors and levels.Finite element analysis was performed according to the table,and the results were recorded.MINITAB was used to analyze the results,and the main optimized parameter combinations were determined with reference to the main effects plot and interaction plot.(5)Using a multidisciplinary optimization platform,the structure of the designed damper was optimized based on multiple objectives.An automatic optimization platform was built by integrating CATIA,MATLAB,and ISIGHT.The optimization objectives were to minimize the working cylinder volume,reduce power consumption,increase damping force at low speed,and increase the dynamic adjustable range.A multi-objective genetic algorithm(NSGA-Ⅱ)combined with a generalized gradient algorithm(LSGRG)was proposed for optimizing the damper.The results demonstrated that the optimization strategy combining NSGA-Ⅱ and LSGRG produced better optimal solutions than using NSGA-Ⅱ alone.Finally,the optimal solution was verified through finite element analysis of electromagnetic fields.