Hybrid Damping Mode MR Damper: Development and Experimental Validation with Semi-Active Control

Abstract

This study introduces a novel magnetorheological (MR) damper for semi-active vehicle suspension systems that enhance ride comfort and handling stability. The proposed damper integrates reverse and normal damping modes, enabling independent control of rebound and compression strokes through an external MR valve. This configuration supports four damping modes—Soft/Soft, Hard/Soft, Soft/Hard, and Hard/Hard—allowing adaptability to varying driving conditions. Magnetic circuit optimization ensures rapid damping force adjustments (≈10 ms), while a semi-active control algorithm incorporating skyhook logic, roll, dive, and squat control strategies was implemented. Experimental validation on a mid-sized sedan demonstrated significant improvements, including a 30–40% reduction in vertical acceleration and pitch/roll rates. These enhancements improve vehicle safety by reducing body motion during critical maneuvers, potentially lowering accident risk and driver fatigue. In addition to performance gains, the simplified MR damper architecture and modular control facilitate easier integration into diverse vehicle platforms, potentially streamlining vehicle design and manufacturing processes and enabling cost-effective adoption in mass-market applications. These findings highlight the potential of MR dampers to support next-generation vehicle architectures with enhanced adaptability and manufacturability.

1. Introduction

A vehicle’s suspension system is responsible for insulating vibrations and shocks transmitted from road input to the body carrying passengers and effectively suppressing the body’s roll, pitch, and bounce movements caused by the driver’s driving actions, such as steering, braking, and driving. In addition, it appropriately controls the movement of the wheels to optimally maintain the contact force between the tires and the road surface during steering and braking. In order to effectively perform these functions, a suspension system that can provide optimal damping force under various driving conditions is required.

Active suspension systems can generate both damping and active forces in either direction. However, they typically require substantial energy input, complex actuators (e.g., hydraulic or electric), and advanced safety mechanisms. While numerous studies have demonstrated the performance advantages of active suspension systems [1,2], their adoption in passenger vehicles remains limited due to high costs, energy demands, and packaging constraints. In contrast, semi-active suspension systems adjust damping forces in real time by controlling variable valves without actively injecting energy into the system. This enhances energy efficiency and simplifies actuator design. In particular, magnetorheological (MR) fluid-based semi-active suspensions have demonstrated strong potential for improving both ride comfort and handling stability, owing to their rapid response characteristics and broader controllable damping range compared to conventional hydraulic systems [3,4]. Accordingly, this study focuses on the development and experimental validation of an MR-based semi-active suspension system that achieves fast, adaptive, and energy-efficient control, while ensuring robustness and feasibility for vehicle-level integration. Compared to conventional semi-active systems based on step motors or proportional solenoids, MR-based dampers offer superior response times (typically 10–20 ms) and greater control bandwidth, making them more effective for high-frequency dynamic response control.

Semi-active variable dampers utilizing step motors or proportional solenoids have been developed and used to overcome these limitations. However, these mechanical methods have the disadvantage of being unable to show fast response (approximately 50–80 ms) enough to control wheel movement due to the influence of hydraulic and mechanical inertia. To improve the complexity and performance of such hydraulic-based dampers, many studies have been conducted on various aspects using MR fluid.

From the perspective of damper actuator development, research has been conducted to improve response performance, change the MR fluid force-generating structure, and study damper modeling. In addition, research and development to improve the fluid’s characteristics are continuously being conducted.

Precise numerical modeling of the nonlinear behavior of MR dampers was proposed, a verification study through experiments was conducted [5], and a method to numerically express the nonlinear hysteresis of MR dampers through experimental-based Bouc–Wen modeling was proposed [6]. Yang discussed integrating nonlinear negative stiffness elements in a semi-active suspension system using MR dampers and emphasized the potential improvement of vibration suppression performance due to the nonlinearity introduced into the suspension system [7]. This study shows how the mechanical design’s sophistication optimizes dampers’ adaptive response and improves their functional characteristics under various conditions. Furthermore, the nonlinear dynamics associated with these designs explored by Zhang consider the chaotic response and stability of various periodic solutions based on the dynamics of suspension systems incorporating MR dampers [8].

Advances in damper design and manufacturing methods also affect the operational efficiency of MR dampers. Park presents a novel rotary MR damper tailored for low-floor vehicle suspension systems and compares its torque characteristics with conventional linear MR dampers. This rotary design is known for its potential practicality in specific applications, and it offers more space and weight management efficiency than linear configurations. Studies have shown that the responsiveness of MR dampers can be significantly improved by adjusting the flow rate and pressure drop through innovative bypass and orifice designs, providing an adjustable damping force that adaptively responds to input conditions [9]. Wang analyzed the damping force energy composition under impact conditions and verified the robust performance of MR dampers by adopting a dual-rod structure [10]. Zhang proposed optimizing the flow path and increasing the magnetic field utilization as the development direction of embedded MR dampers and proposed the design direction of bypass hydraulic circuits to secure a wide range of damping force. It was emphasized that securing MR fluid temperature robustness, weight reduction, and high damping force are necessary for expanding future application fields [11]. In addition, research was conducted on damper system identification and additional power transmission structure proposals, including multiple relief orifices to reduce the initial peak or increase the magnetic field [12,13,14,15].

The optimization of MR damper performance extends to control strategies, which have become a major concern for many researchers. A variety of control techniques, ranging from simple on-off control to advanced optimization methods such as linear quadratic regulator (LQR) and adaptive backstepping control, have been developed to effectively manage the operating characteristics of MR dampers [16,17,18,19,20,21]. Soliman reviews the development of these control strategies and points out that as the complexity of applications increases, the precision and responsiveness of control systems for real-time vibration mitigation must be improved [4]. Meanwhile, Yan presents a modern approach to address the nonlinear characteristics of MR dampers through his study of the use of neural networks for developing inverse control models, paving the way for improved precision of damping response [22]. Mousavi discusses the limitations of conventional control methodologies due to the inherent nonlinearity of MR dampers and emphasizes that intelligent inverse models are essential for effective control in semi-active vibration isolation applications [23].

Haiping applied a polynomial-based MR damper model and proposed H-infinity control based on static output feedback to reduce the number of sensors and improve practicality [3]. Zapateiro proposed two control methodologies suitable for suspension systems based on semi-active control, namely, adaptive backstepping control and quantitative feedback theory (QFT), considering the nonlinear characteristics of the damper [24]. Wu verified the expansion of design area utilization and the improvement of frequency control area performance according to load state by designing a control structure for applying the nonlinear characteristic constraints of MR dampers in real-time and an adaptive Lyapunov matrix and feedback gain according to load state [25]. Feng proposed an adaptive backstepping control logic that compensates for the time delay problem in the control loop in real time to secure stability and ride comfort in MR seat suspension [26]. Diaz-Choque proposed an adaptive control technique that integrates an artificial neural network (ANN) that adjusts PID gains in real-time in a semi-active suspension system based on MR dampers to solve the balance problem between ride comfort and steering stability, which is essential for autonomous driving and luxury vehicles [27].

Tang emphasized the importance of the Takagi–Sugeno fuzzy control approach for semi-active MR dampers [28], and Tharehalli Mata proposed the superiority of the Optimal Sliding Mode control performance [29]. The parametric black-box modeling of these dampers described by Kasprzyk provided a useful framework for predicting damping behavior based on real-time inputs and suggested that it could be utilized in adaptive system applications [30]. Fernando Oliveira et al. applied MR dampers to seismic structures and confirmed real-time control improvement with simple logic by introducing the Force Tracking Integral + Clipped On–Off (COO) method instead of the existing complex algorithm [31]. Gad proposed a seat MR damper current prediction controller using two types of neural networks (P-ANN, Q-ANN) to improve the control accuracy [32]. In addition, a study was conducted to propose a non-parametric damper modeling based on ANFIS (Adaptive Neuro-Fuzzy Inference System) to solve the adaptive limitation through lightweight and BPNN-based PID control that is advantageous for real-time control and reinforcement learning [33,34]. Regarding the application of MR dampers, there was a claim that it is necessary to reduce the cost and complexity of damper manufacturing to apply them to various vehicle types such as electric vehicles and SUVs in the future [35].

This study proposes an MR damper design that can create multiple damping characteristics that can improve vehicle ride quality and handling stability. It was planned to complement the lack of axial/tensile direction control freedom and insufficient verification of actual vehicle applicability presented in previous studies. In particular, this study was conducted using the following technical directions, focusing on securing real-time control response and various damping force mode MR dampers.

• Independent Control of Rebound and Compression Damping:

By designing an independent damping force control structure utilizing an external MR valve rather than the existing built-in MR valve method, independent damping force control between rebound and compression strokes was enabled. Four damping modes (Soft/Soft, Hard/Soft, Soft/Hard, Hard/Hard) were implemented. This structure is expected to secure flexibility in applying vehicle dynamics control algorithms compared to existing single-mode MR dampers.

• Optimized Electromagnetic Valve Design for Fast Response:

An electromagnetic valve design considering magnetic circuit optimization and response delay minimization was proposed through an external damper design, and the performance level was verified through a response test.

• Integrated Control Logic for Multi-Objective Vehicle Dynamics:

We designed a controller structure that integrates the ride comfort control based on the skyhook algorithm and the anti-roll, anti-dive, and anti-squat control strategies. We developed an algorithm that can perform complex vehicle dynamics control through this.

• Experimental Validation of Temperature Sensitivity and Friction Effects:

We secured basic experimental results on the damping force control performance and the change in MR fluid characteristics according to temperature and the friction increase problem, and it is judged that it will be able to provide basic data for compensation logic or structural supplementation in the future.

2. MR Variable Damper Design

In this chapter, we analyze the principles of force generated in MR fluids and proceed with magnetic field design and valve path design to satisfy the requirements of damper function.

2.1. MR Fluid Characteristics

Magnetorheological (MR) fluids exhibit Bingham fluid properties due to the alignment of particles in the fluid under the influence of an external magnetic field. The Bingham plastic model frequently provides an accurate representation of the flow behavior of ER or MR fluids. The Bingham plastic model can be defined as shown in Equation (1) [36], where η_p is the plastic viscosity, τ_y is the total yield stress, and ${\tau }_{y\left(field\right)}$ is the yield stress induced by an electric or magnetic field. The shear rate, denoted by $\dot{\mathrm{\gamma }}$, is a critical component in the analysis.

$${\tau }_y={\tau }_{y\left(field\right)}+{\eta }_P\dot{\gamma }$$

(1)

2.1.1. Total Stress

The force generation mechanism using MR fluid can be explained in three modes.

• Flow mode

A pressure difference is generated using a mechanism such as a piston to form a fluid flow field through an orifice, a coil is wound around the orifice to supply current to form a magnetic field, and the shear force is changed using the magnetorheological properties of the fluid.

• Shear mode

Flow mode is when the flow of the fluid itself is disturbed, and shear mode is when the movement of the plate outside the fluid is affected

• Squeeze mode

The magnetic force affects the fluid between the plates moving up and down, which affects the compressive strength. Generally, dampers apply the flow mode of MR fluid, and brake systems apply the shear mode (Figure 1).

The electromagnetic field was designed to generate a damping force using the flow mode.

2.1.2. Viscosity Properties

The viscosity of magnetorheological fluid (MR fluid) is sensitive to temperature changes caused by changes in the properties of the carrier fluid and magnetic particles. The increase in the temperature of the fluid reduces the viscosity, which means that the shear transmission performance is attenuated. In addition, the particle chain structure is weakened, which weakens the magnetic interaction, making the structure unstable and reducing the shear resistance. The carrier fluid may evaporate and deteriorate at high temperatures, resulting in low long-term stability. It directly affects the viscosity and shear stress of MR fluid, and, in general, this can significantly impact the performance and applicability of the fluid. At low temperatures, the viscosity generally increases, which can be an important evaluation factor when applied to automobiles, primarily passenger cars, prioritizing ride comfort. In this study, MR fluids were tested in two cases to confirm the effect of temperature on viscosity.

Viscosity measurements were conducted using a Brookfield RVDV-III rotational viscometer with a small sample adapter (SC4-27). The MR fluid was stabilized at each target temperature using a thermostatic bath, and viscosity was measured at two rotational speeds: 1 rpm (Case 1) and 50 rpm (Case 2). The test temperatures were set from −10 °C to 40 °C in 10 °C increments. Each data point represents the average of three repeated measurements to ensure reliability. The viscosity of the MR fluid by speed was low in Case 1, and it can be seen that the viscosity characteristics are similar as the speed increases. In addition, there is a part where the viscosity characteristics increase as the temperature goes below zero, so in this part, there may be a direction to further improve the characteristics of the material properties in the future and a direction to control the temperature compensation of the algorithm (Figure 2).

2.2. MR Damper Design

The most important part of designing a semi-active damper is the damping force variable range and degree of freedom. In order to secure a large damping force range, the magnetic field design must be performed first to satisfy this. Then, the valve that can generate an appropriate damping force can be designed based on the characteristics of the secured magnetic field. In order to generate tension and compression-independent damping forces, it is designed so that separate magnetic field intensities can occur. The magnetic field intensity is designed to be 120,000 H or more, as illustrated in Figure 3.

2.2.1. MR Valve Design

Based on the magnetic flux characteristics, the size of valve shape $A_{core}$, $A_{path}$, $A_{pole}$ as shown in Figure 4, is determined. Here, $A_{core}$ means the minimum transverse cross-sectional area of the piston head (when there is a hole in the center) and can be described as in Equation (2).

$$A_{core}={\displaystyle \frac{\pi D_{core}^2}{4}}({\displaystyle \frac{\pi (D_{core}^2-D_{hole}^2)}{4}})$$

(2)

The minimum transverse cross-sectional area $A_{path}$ of the investment material that determines the path of the magnetic flux is defined in Equation (3) below.

$$A_{path}={\displaystyle \frac{\pi (D_O^2-D_I^2)}{4}}$$

(3)

The surface area $A_{pole}$ of the piston’s stimulus is defined as in Equation (4).

$$A_{pole}=\pi D_{pole}{L}_g$$

(4)

The area ratio of each section is set by considering the BH characteristics of the tube material through which the core part and the MR fluid are returned, and the optimal density $B_{opt}$ is derived from the BH characteristics of the MR fluid. That is, it is to satisfy the geometric shape conditions so that the optimal magnetic flux is generated and is smaller than the saturation magnetic flux ${Ø}_{sat}$. The inherent magnetic flux density $B_{intrisc}$ of the MR fluid is shown in Equation (5) below [36,37]. The corresponding BH and B–J characteristics are depicted in Figure 5.

$$J=B_{\begin{array}{c}Intrinsic\end{array}}=B-{\mu }_{0}H$$

(5)

The optimal B value $B_{opt}$ is obtained through the magnetic field intensity $H_c$ at the point determining the Secant slope in the J vs. B diagram. Through experiments, it can be seen that the MR fluid characteristic occurs at a value of 100,000 [A/m] (1300 [Oe]) with a quantity of 0.635 [t] (6350 [gauss]). Although the magnetic field strength at the MR fluid gap was designed to exceed 120,000 A/m based on magnetic circuit analysis, experimental measurements indicated a value of approximately 100,000 A/m. This discrepancy could be attributed to several factors, including localized variations in the magnetic permeability of SUS430 due to manufacturing processes, flux leakage and fringing effects not considered in the analytical model, and potential sensor alignment errors within the narrow gap region. In addition, the 2D simulation model applied in this study does not fully reflect geometric irregularities or asymmetries in the real three-dimensional valve structure. These combined effects may cause the observed 15–20% deviation.

$B_{knee}$ is the saturated critical flux density of the core and tube material, SUS430, and has a quantity of 14,000 [gauss]. The ratio of the two flux densities $B_{opt}$ and $B_{knee}$ is as in Equation (6), and the flux $Ø$ can be defined as in Equation (8).

$$Ratio={\displaystyle \frac{B_{opt}}{B_{knee}}}=0.6$$

(6)

$${\displaystyle \frac{A_{core}}{A_{pole}}}={\displaystyle \frac{\pi D_{core}^2}{4}}\times {\displaystyle \frac{1}{\pi D_{pole}g}}, and {\displaystyle \frac{A_{path}}{A_{pole}}}={\displaystyle \frac{\pi (D_O^2-D_l^2)}{4}}\times {\displaystyle \frac{1}{\pi D_{pole}g}}={\displaystyle \frac{B_{opt}}{B_{knee}}}$$

(7)

$$\varphi =B_{knee}{A}_{core}=B_{opt}{A}_{pole}$$

(8)

The core area and the tube area should be selected so that the magnetic flux density between the paths of the MR fluid, which becomes the operating point when the magnetic flux $Ø$ is the same and the critical magnetic flux density of SUS430 is formed, is greater than the above ratio. The energy $E_f$ accumulated in the MR fluid can be defined as in Equation (9) [36,37].

$$E_f={\displaystyle \frac{1}{2}}{B}_f{H}_f{V}_f={\displaystyle \frac{1}{2}}{B}_f{H}_f·2A_{pole}·g$$

(9)

The energy $E_s$ accumulated in steel (SUS430) can be defined by Equation (10) [36,37]. Here, $L_s$ is the length of the magnetic flux passing through the steel, and it should be designed so that when current is applied, the magnetic energy is accumulated on the fluid side rather than on the steel.

$$E_s={\displaystyle \frac{1}{2}}{B}_s{H}_s{V}_s={\displaystyle \frac{1}{2}}{B}_s{H}_s·2A_{core}·L_s$$

(10)

$${\displaystyle \frac{E_f}{E_s}}\approx {\displaystyle \frac{\frac{1}{2}{B}_f{H}_f{A}_{pole}\mathit{g}}{\frac{1}{2}{B}_s{H}_s{A}_{core}{L}_s}}={\displaystyle \frac{2H_f\mathit{g}}{H_s{L}_s}}$$

(11)

2.2.2. MR Valve Damping Force

The MR fluid flowing between the gaps becomes plasticized under the influence of the magnetic field, and the pressure difference $∆P_{\tau }$ corresponding to the shear force ${\tau }_{y\left(field\right)}$ to overcome this and allow the MR fluid to flow can be derived using the magnetic field strength H in Equation (12). In addition to conventional models such as Bingham or Bouc–Wen, recent studies have proposed alternative modeling approaches to better capture the nonlinear hysteretic behavior of MR dampers. For example, Viadero-Monasterio et al. [38] introduced a tanh-based MR damper model integrated with a robust static output feedback controller, demonstrating improved estimation accuracy and real-time control performance compared to Bingham and bi-viscous models. The final internal pressure difference is calculated as in Equation (14) [36,37]. Figure 6 illustrates the pressure variation of the MR damper due to fluid flow under magnetic field excitation; the red path indicates the flow region where the pressure drop occurs due to field-induced shear resistance.

$$\begin{array}{c}{\tau }_{y\left(field\right)}=a{H}^x\\ a=8.37\times {10}^{-6}, x=1.32\end{array}$$

(12)

$$A_{path}={\displaystyle \frac{\pi (D_O^2-D_I^2)}{4}}$$

(13)

$$\Delta P_{\tau }={\displaystyle \frac{c{\tau }_{y\left(field\right)}L}{g}}$$

(14)

Figure 3 shows a double-path valve model designed with two core parts, the upper part with the magnetic path facing clockwise and the lower part with the magnetic path facing counterclockwise. The overall size was increased, the core center area $A_{core}$ was secured to prevent the magnetic saturation phenomenon, and the gap height $L_g$ was secured to increase the area where shear stress acts, thereby securing damping force. The results showed that the gap’s magnetic field strength H value acts over 100,000 [A/m], and the magnetic saturation phenomenon occurs when the current is over 5 [A].

2.3. Damper Design with MR External Valve

The external MR valve is designed in the same way as the internal valve. However, since it is installed inside the damper, it is advantageous in terms of installation. However, since the damping force ratio during the compression/extension stroke is fixed, there is a disadvantage in that the degree of freedom is very low when tuning the actual vehicle performance. A method was designed to install the damping valve for the tension/compression stroke separately/separately on the outside of the damper. This method can have four damping force modes: Soft/Soft, Hard/Soft, Soft/Hard, and Hard/Hard, and has the advantage of doubling the system’s responsiveness. In other words, switching according to the wheel’s movement, which requires fast responsiveness, is performed automatically by separating the compression/extension damping force valve. The flow path is designed so that the fluid from the rebound chamber can move to the compression chamber side through two paths during the tension stroke of the damper, and it consists of two paths: passing through the gap of the rebound MR valve and passing through the slit valve and disk valve on the piston side. During the compression stroke, the fluid passes through the gap of the compression MR valve in the compression chamber and moves to the base chamber through the body valve in the same way as during the tension stroke. The MR valve side controls the damping force of the low-speed range that the semi-active damper requires, and the high-speed range is designed to be controlled by the piston inside the damper and the body valve side. The type and number of valve coils were selected so that the voltage supplied from the vehicle is 12 [V], and the DC resistance inside the valve is minimized to maximize the heat generation rate. The overall layout of the damper assembly and external MR valves is shown in Figure 7.

3. MR Damper Performance Validation

3.1. Responsiveness and Friction Characteristics

The MR valve responsiveness was measured to be approximately 10 [ms] (90% arrival time for step input), as shown in Figure 8. Two function generators were used to generate the PWM control signal—one producing a PWM waveform and the other generating a square wave. These signals were processed through an AND gate logic circuit to create a 10 Hz square-wave PWM signal, which was supplied to the PWM driver of the MR damper. The damper was installed on a damper performance tester and excited at constant piston velocities ranging from 0.05 m/s to 0.6 m/s. The damping force, piston velocity, and square-wave input signal were acquired during this test using the tester’s internal sensors and an FFT analyzer. The measured response curve was used to analyze the response time of the MR damper under periodic current excitation. Considering the operational responsiveness of 40 to 50 ms of the mechanical valve used in the existing semi-active type, it is judged to have secured sufficiently fast responsiveness, and this is because the generation of damping force is directly matched with the response characteristics of the electromagnetic force. The biggest concern when configuring a damper using MR fluid is the increased friction force, which must be reviewed.

A low-speed sinusoidal excitation was applied at a velocity of 0.01 m/s, and the excitation displacement is ±5 mm using the damper test system. The resulting resistive force—measured without current input—was interpreted as friction force, including seal resistance and fluid shear under no magnetic field. This low-speed condition allowed the isolation of frictional effects from dynamic damping behavior; the result is shown in Figure 9. Since it is large compared to less than 5 [kgf] of the existing general oil mass-produced damper, a method to reduce the friction force should be considered in the future.

The achieved fast response time of approximately 10 ms, compared to the typical 50 ms of conventional MR dampers, is primarily enabled by the optimized magnetic circuit design and independent rebound/compression external MR valves. This structural decoupling reduces magnetic path saturation and allows for more rapid field modulation. Furthermore, the double-path external valve configuration enhances fluid responsiveness by eliminating hydraulic delay and reducing electromagnetic inertia. These enhancements are critical for extending semi-active control bandwidth for ride comfort and future wheel-domain vibration control strategies in autonomous and electric vehicles.

3.2. Damping Force

The damper was mounted on a damper performance test system and subjected to sinusoidal excitation with a ±20 mm displacement amplitude. The excitation frequency was adjusted to produce piston velocities ranging from 0.05 m/s to 1.2 m/s. For each test, a predetermined current level (0 A to 3 A in 1 A increments) was applied to the solenoid coil before excitation began, and the corresponding damping force was recorded using a load cell. This allowed the evaluation of current-dependent force output at different operating speeds for rebound and compression strokes.

Figure 10 and Figure 11 show tests in which the damping force was measured by increasing the current applied to the rebound and compression valves in the speed range of 0 to 1.2 m/s. It can be seen that the damping force increases linearly and proportionally as the current applied to the valve increases, and it can be seen that the tension and compression damping forces are independently controlled. In addition, it can be confirmed that the tension-compression low-speed (0.05 m/s) damping force of 155/55 kgf for the initial vehicle attitude control can be secured.

3.3. Limitations and Optimal Operating Conditions

Although the developed MR damper exhibits advantageous features such as rapid actuation (~10 ms), wide-range damping modulation, and stroke-specific force control, several practical limitations remain. Firstly, the internal friction generated by the interaction between suspended magnetic particles and mechanical components (e.g., seals, piston rings) is measurably higher than that of conventional hydraulic dampers. This elevated friction is especially detrimental in fine-stroke, low-speed oscillation scenarios, where excessive damping may compromise ride quality. Second, temperature fluctuations can change the damping force generated by changing the responsiveness to magnetic fields within the MR fluid. This influence of temperature changes can be particularly important during initial operation in low-temperature environments or when it is difficult to maintain consistent damping behavior under sustained high-temperature conditions. Thirdly, while the actuator maintains linear force modulation within its nominal operating range, saturation phenomena may appear under rapid, large-displacement excitations, limiting its authority during aggressive maneuvers such as evasive lane changes or harsh braking.

In its current form, the system performs most effectively within typical ambient and drivetrain temperature bands (approximately −30 °C to +80 °C) and under transient maneuvers not exceeding mid-frequency road inputs. Performance attenuation is expected under continuous high-frequency vibrations or when the thermal envelope is exceeded. To extend applicability across broader operational conditions, future efforts should emphasize reducing tribological losses, enhancing the thermal robustness of the MR fluid, and increasing the system’s saturation threshold through design and control co-optimization.

4. Vehicle Control Logic

In order to improve the driving performance of the vehicle using the previously developed MR actuator, the control logic applied to the semi-active suspension device was developed. The control logic is divided into sub-modules for each vehicle’s behavior and control purpose. It mainly comprises ride control logic, speed-sensitive control logic, anti-roll control logic, anti-dive control logic, and anti-squat control logic. Figure 12 shows a configuration diagram between each sensor and the logic installed in the system. A total of 7 sensors are used, including a vertical acceleration sensor, steering angle sensor, vehicle speed sensor, brake on/off sensor, and throttle position sensor.

4.1. Overall Function Module

The skyhook damping and speed-sensitive logic control the ride comfort in real-time. When handling and acceleration/deceleration situations are added, the required damping force of each is synthesized, and the control is performed by considering the priority. Since each damper has an independent tension/compression MR valve, eight solenoid current controls are performed.

4.1.1. Ride Comfort Logic

The purpose of the ride control logic is to control vehicle motion by suppressing resonance for road input in the body resonance region and to improve ride comfort by softening the damping force in the road input in the ride comfort region. This logic is applied independently to each wheel and uses three vertical sensors mounted on the body. One part not equipped with a vertical acceleration sensor is estimated from three body vertical accelerations. The signal output from the sensor is used to calculate the velocity using an integrator, and the required ride value is calculated using the RMS value of the velocity. The determination of the damper damping force is based on the skyhook logic [39,40]. The ride value is multiplied by the vertical velocity of the body. It acts as a factor that varies according to the frequency and size of the road surface, and the body’s vertical velocity $v_i$ applied to the skyhook logic is weighted for the frequency.

$${DF}_{ride}\left(v_i\right)=\left\{\begin{array}{cc}{K}_{ride,reb}\hspace{0.17em}{\overline{v}}^{\hspace{0.17em}h},& \mathrm{if} v_i>0,\\ K_{ride,comp}\hspace{0.17em}{\overline{v}}^{\hspace{0.17em}h},& \mathrm{if} v_i<0,\end{array}\right.$$

(15)

• $v_i$: Current body vertical velocity
• ${\overline{v}}^{\hspace{0.17em}h}$: Low pass filtered absolute body velocity
• $K_{ride,reb}, K_{ride,comp}$: Skyhook gain for each rebound and compression side

Variable damping force dampers can be divided into two types according to the damping force variation state. A normal continuously variable damper produces a hard damping force at the rebound and compression strokes, and a reverse continuously variable damper produces a large damping force on only one stroke side. The reverse continuously variable damper is suitable from the perspective of the skyhook application. Its structure is designed to be a reverse damper with a variable damping mechanism that has a soft-hard section where the rebound damping force is soft, and the compression damping force is hard, a soft–soft section where both are soft, and a hard–soft section where the rebound damping force is hard, and the compression damping force is soft (Figure 13).

$$\begin{gathered} \mathrm{If} {\dot{z}}_s({\dot{z}}_s-{\dot{z}}_u)<0 \mathrm{then} \mathrm{SOFT} \mathrm{Damping} \\ \mathrm{Else} {\dot{z}}_s({\dot{z}}_s-{\dot{z}}_u)>0 \mathrm{then} \mathrm{HARD} \mathrm{Damping} \end{gathered}$$

(16)

where ${\dot{z}}_s$ represents the vertical velocity of the sprung mass, and ${\dot{z}}_u$ represents the vertical velocity of the unsprung mass. When ${\dot{z}}_s$ is positive, the piston speed (the relative velocity of the sprung mass and the unsprung mass) can also positive depending on ${\dot{z}}_u$. If ${\dot{z}}_s-{\dot{z}}_u$ is positive, the damping force should be hard; if it is negative, it should be soft. On the contrary, when ${\dot{z}}_s$ is negative, if ${\dot{z}}_s-{\dot{z}}_u$ is positive, it should be soft; if it is negative, it should be hard. Therefore, the logic is designed so that the hard–soft mode is applied when ${\dot{z}}_s$ is positive, and the soft–hard mode is converted when ${\dot{z}}_s$ is negative so that the body’s up-and-down movement is controlled even without information about ${\dot{z}}_u$.

4.1.2. Handling Control Logic

The handling control logic suppresses the vehicle’s roll motion by increasing the damping force of the left and right dampers when steering the vehicle. It detects the driver’s steering input from the steering angle sensor and controls the transient region of the body’s behavior. The lateral acceleration can be defined as in Equation (14), and the ${\displaystyle \frac{{\dot{\delta }}_{sw}}{i_s}}$ term is the part that converts the driver’s steering input (steering wheel angular velocity) into the actual wheel steering angular velocity considering the gear ratio. The ${\displaystyle \frac{1}{1+{\left(V/V_{ch}\right)}^2}}$ term adjusts the lateral acceleration by the ratio of the vehicle characteristic speed ($V_{ch}$) and the actual driving speed ($V$), and the value of this term decreases as the driving speed increases, reflecting the decrease in the lateral acceleration sensitivity at high speeds. The roll value is obtained by calculating the change in lateral acceleration based on the lateral acceleration calculated as in Equation (17). Calculating the change in lateral acceleration is necessary because the damping force depends on speed.

$$\begin{array}{cc}{a}_y& ={\displaystyle \frac{V^2}{l}}·{\displaystyle \frac{1}{1+{\left(\frac{V}{V_{ch}}\right)}^2}}·{\displaystyle \frac{{\dot{\delta }}_{sw}}{i_s}},\end{array}$$

(17)

$$\begin{array}{cc}{DF}_{roll}& =\left|K_{roll}·{\displaystyle \frac{d}{dt}}(a_y)\right|\end{array}$$

(18)

• $a_y$: Vehicle lateral acceleration [m/s²]
• $V$: Vehicle speed [m/s]
• $l$: Wheelbase [m]
• $V_{ch}$: Vehicle characteristics speed [m/s]
• $\dot{{\delta }_{sw}}$: Steering wheel angle rate [deg/s]
• $i_s$: Steering gear ratio

Reverse mode can implement skyhook control using a small number of sensors, but it has limitations in implementing the anti-roll control required for stable steering control. It has a disadvantage in that it cannot stably handle transient conditions when steering changes suddenly, such as in the case of a double lane change. Therefore, if normal mode using rebound/compression hard damping that utilizes fast response is utilized, anti-roll control can be implemented stably. Since rebound and compression valves are currently used independently, the advantages of both reverse and normal modes can be utilized.

4.1.3. Squat and Dive Prevention Under Acceleration and Deceleration

The squat control logic detects a sudden change in the vehicle throttle opening angle and controls the vehicle pitch motion that occurs at that time. It differentiates the signal from the TPS sensor and calculates the squat value using this. In order to control the pitch motion that occurs when the vehicle suddenly brakes, the brake on/off sensor and the vehicle speed sensor detect sudden braking of the vehicle and hard adjust the damping force when the vehicle decelerates more than the set deceleration rate to reduce the vehicle behavior.

4.2. Ride Comfort Simlation

The performance of the ride comfort control logic is verified using a half-car-based vehicle model, and the simulation results are shown in Figure 14. It can be seen that the displacement of the vehicle body converges with a smaller fluctuation in the case of the Semi-Active ECS than in the case of the Conventional ECS. It can be seen that the skyhook control is performed using the characteristics of the reverse damper. It can be seen that the skyhook control is automatically performed by the characteristics of the damping force switching mode of the MR damper when the control is performed based on the sign of the vertical velocity of the body. The control amount of the damper hardware can be adjusted independently of tension and compression, which can expand the tuning freedom and damping force variable range.

Table 1. Vehicle parameters for ride comfort simulation.

Symbol	Value	Unit	Description
$m_{fs}$	427.5	kg	Front sprung mass
$m_{rs}$	251	kg	Rear sprung mass
$m_u$	41.5	kg	Unsprung mass
$I_{\theta }$	443	kg∙m2	Pitch moment of inertia
$k_f$	38,000	Ns/m	Equivalent front spring stiffness
$k_r$	18,000	Ns/m	Equivalent rear spring stiffness
$k_t$	211,800	N/deg	Tire vertical stiffness
$C_r$	97,500	N/deg	Rear tire cornering stiffness
$l_f$	1.483	m	Distance from center of gravity to front axle
$l_r$	1.5189	m	Distance from center of gravity to rear axle

shows the vehicle parameters used in the simulation model. Figure 15 shows the reverse damper mode transition diagram when performing skyhook control using reverse mode damping when a vehicle passes over a bump.

4.3. MR Solenod Valve Control

Each wheel’s MR damper control logic command is converted into a PWM signal using the current table to drive the solenoid valve. A multifunction driving element was used to enable solenoid driving at the TTL level. In addition, the Current Feedback method, which detects the current flowing through the solenoid and adjusts the PWM amount, was used to perform optimal control. The driving unit is driven by an independent 8-channel linear feedback current control, and the 8-bit calculated value from the MCU passes through the amplifier and comparator to change the duty and supply it to each driving unit. The driving status of each load is received as Current Feedback and controlled by compensating for it. The solenoid current error is defined as in Equation (16), and the current control is configured as a PI controller as defined in Equation (17). The analog control signal $u\left(t\right)$ is converted into a digital $PWM$ duty ratio $d\left(t\right)$ and transmitted to the actual driving unit. The effective voltage $d\left(t\right)·V_{in}$, which is determined by the duty ratio $d\left(t\right)$, is applied to the coil, causing the current $i_s$ to change.

$$e(t)=i_{ref}(t)-i_s(t)$$

(19)

$$u(t)=K_p\hspace{0.17em}e(t)+K_i{\int }_0^{t}e\left(\tau \right)\hspace{0.17em}d\tau$$

(20)

$$d\left(t\right)=PWM\left(u\left(t\right)\right)$$

(21)

$$L{\displaystyle \frac{d\hspace{0.17em}{i}_s(t)}{dt}}+R\hspace{0.17em}{i}_s(t)=d(t)\hspace{0.17em}{V}_{in}$$

(22)

5. Vehicle Test

A mid-sized car was equipped with sensors and MR external valve dampers. The vertical G sensor and steering angle sensor were products applied to the ECS (semi-active electronic control system) that were mass-produced in the past. The controller was implemented as an embedded ECU, and an additional environment was configured for tuning the actual car. The overall schematic is shown in Figure 16.

5.1. Ride Comfort

A bump road test was conducted at the proving ground to evaluate ride comfort performance using a full-scale test vehicle equipped with the proposed MR damper system. The test road consisted of standardized trapezoidal speed bumps with a height of 80 mm and spacing of 1.5 m. The vehicle was driven at two constant speeds (20 kph and 30 kph), and the vehicle’s dynamic response was measured while passing over the bumps. It shows how stably the vehicle passes through the control and non-control states by how much the peak-to-peak values of the vertical acceleration component $A_z$ and the pitch rate ${\omega }_y$ component of the body decrease. They are 30% and 40% smaller in the control state than in the non-control state, respectively, showing that the vehicle attitude changes less and passes through under control. Figure 17a,b show the test results when the vehicle speed is 20 and 30 kph. In particular, it shows that after passing over the bump, the attitude stabilizes immediately without any change in the attitude in the control mode.

5.2. Handling Performance

The handling performance was evaluated by applying a manual sinusoidal steering input of ±50° at 1 Hz while maintaining a constant vehicle speed of 60 kph. This steering input induces continuous lateral load transfer and excites roll dynamics representative of mid-speed maneuvering conditions. The vehicle’s lateral acceleration and roll rate were measured during the test using onboard inertial sensors.

The test was conducted under three different control modes: Firm–Firm mode (high damping in both rebound and compression), Firm–Soft mode (firm rebound and soft compression damping), and Non-Control mode (passive baseline). These modes were implemented using the independently controlled MR dampers on each suspension. By comparing the roll responses across these modes, the effect of damping configuration on lateral stability and body control was evaluated in terms of roll amplitude and damping behavior.

As shown in Figure 17, the controlled modes showed reduced lateral acceleration amplitudes and approximately 30% lower roll rate compared to the non-controlled case. In Figure 18, the Firm–Soft (Reverse) mode achieved better roll suppression than the passive baseline, while the Firm-Firm (Normal) mode showed the lowest roll rate overall. This demonstrates the advantage of symmetric high damping in controlling body roll during repetitive lateral loading.

In the MR semi-active system used in this study, the rebound and compression damping forces can be independently adjusted to Firm or SOFT states. This allows for directional control strategies such as skyhook and anti-roll implementations. However, the H/S configuration with reversed damping may be insufficient to maintain better roll stability under lateral steering conditions. In contrast, the H/H configuration enables balanced left–right damping control, effectively minimizing vehicle roll and helping to stabilize the roll center trajectory during steering maneuvers.

5.3. Sudden Acceleration and Deceleration Performance

When the terminal acceleration drops sharply to a negative value due to sudden braking, the vehicle’s load transfers to the front wheels, causing the vehicle to dive forward. The vehicle deceleration at this time is calculated, and the front/rear damping is changed to Hard, stabilizing the vehicle’s attitude with a pitch rate that is reduced by 30%, as shown in Figure 19a. When the terminal acceleration drops sharply to a negative value due to sudden braking, the vehicle’s load transfers to the front wheels, causing the vehicle to dive forward. In this test, the vehicle was driven at a constant speed of 60 kph and subjected to full brake input to simulate an emergency stop scenario.

Figure 19b shows the effect of the vehicle attitude when the vehicle suddenly starts. At this time, the vehicle’s load moves to the rear wheels, causing the vehicle to squat. In the acceleration test, the vehicle started from rest, and the throttle pedal was applied to achieve a longitudinal acceleration of approximately 0.4 g. The pitch rate value shows the change in vehicle attitude when the terminal acceleration increases to a positive value. In the case of the control mode, it shows that the vehicle motion occurs stably with a decrease of about 35%. The driver’s will to accelerate is considered a feedforward term using the throttle position sensor value, and the vehicle’s behavior is stabilized by applying an additional feedback term to the acceleration that occurs.

6. Conclusions and Future Works

In this study, we proposed an MR damper that can implement reverse and normal hybrid damping and set four damping force modes to implement skyhook control and steering stability control easily. In addition, to secure a fast response of 10 ms and wide damping force variable range compared to 50 ms of MR general hydraulic damper response, MR fluid and damper design and major performance-influencing factors were analyzed to perform valve path optimization. It was confirmed through temperature, response, friction, and damping force tests that fluid characteristics directly affect temperature and friction. Since the structure of the valve that generates damping force in the MR damper is simpler than that of general hydraulic dampers, the tension/compression independent valve configuration does not significantly affect realistic installation.

In experimental validations using a mid-size passenger vehicle, the proposed system demonstrated a 30–40% reduction in vertical acceleration, pitch, and roll rates under various driving conditions, confirming the effectiveness of the proposed hardware and control strategy. The independently controlled rebound and compression MR valves allow flexible tuning across driving modes, enabling smooth transitions between comfort- and handling-oriented damping characteristics.

We have examined the parameter influence of MR fluid for laboratory experiments from the perspective of damper performance. However, it is believed that continuous research is needed to improve the sensitivity of viscosity changes to low and high temperatures, even at the commercial level. At the same time, friction-induced wear caused by magnetic particle agglomeration may degrade the damper’s long-term durability.

In the future, to secure various damping force tuning freedoms for each vehicle, it is judged that some hydraulic valve integration methods will be necessary based on the MR damping mechanism. Additional research will be conducted on improving secondary ride area control by utilizing the high response characteristics of the MR actuator, and a study will be conducted on predicting damping force in real time through MR damper and fluid state estimation.