Active Hydro-pneumatic Suspension Research Articles

Pitch stability control of variable wheelbase 6WID unmanned ground vehicle considering tire slip energy loss and energy-saving suspension control

Acceleration on a ramp and emergency braking are common driving conditions for special vehicles. Due to the complex coupling between the suspension and the chassis structure, the body attitude maintenance and stability control face huge challenges. Aiming at the control problem of pitch stability of the existing six-wheel independent drive unmanned vehicle (6WID UGV) with variable wheelbase during acceleration and deceleration, this paper designs an interconnected active hydro-pneumatic suspension (IAHPS) that can autonomously adapt to the change of wheelbase. Based on this system, a pitch stability control strategy considering the lowest energy consumption of the chassis is proposed. Firstly, a PID-type sliding mode controller (SMC) is used in the upper controller to calculate the desired anti-pitching torque. The disturbance caused by the nonlinearity and uncertainty of the model is estimated by the extended state observer (ESO). Secondly, with the goal of minimizing the energy consumption of the suspension system, the PSO algorithm is used in the middle controller to decide the pressure of the two accumulators in IAHPS. Thirdly, the lower controller again uses the PSO algorithm to achieve wheel torque distribution to minimize tire slip energy loss; Finally, simulation tests in multiple scenarios verify the effectiveness of the designed layered control strategy in terms of the pitching stability control. Under random road and horizontal road, the energy consumption for active adjustment of suspension is reduced by 28.35% and 29.41% respectively; The total energy loss of tire slip is reduced by 65.16% and 41.52%.

Vertical load distribution strategy of amphibious wheel-track vehicle using neural network and particle swarm optimization

Amphibious wheel-track vehicle (AWTV) can change the vertical load of the wheels and the tracks through the active hydro-pneumatic suspension system, which shows significant advantages in terms of maneuverability and road passing ability. However, AWTV is a strong nonlinear system. The irregularity of the road, and coupling characteristics between the vertical load of the wheel-tracks and the terrain will greatly affect the tractive efficiency of the whole vehicle. Therefore, how to effectively distribute the vertical load between the wheel and the track to improve the tractive efficiency of the whole vehicle is still a huge challenge. To address the above problems, based on the neural network (NN) and particle swarm optimization (PSO) algorithm, vertical load distribution strategy of the AWTV is proposed to improve its traction efficiency under different driving road in this paper. Firstly, the coupling dynamics model of AWTV with road and hydraulic system dynamics model of active suspension is established; Secondly, the wheel-track terrain model is built in EDEM-Recurdyn to collect data of vertical load and traction efficiency under the different soils and speeds, and the coupling function is obtained through NN; Then, the optimal vertical load of each axle is optimized through PSO; Finally, the feasibility and effectiveness of the strategy are verified by the simulation analysis under different road conditions and distribution strategies. The simulation and test results demonstrate that the proposed vertical load distribution strategy based on NN-PSO can effectively improve the traction performance of the AWTV in complex terrain environment, and have relatively superior control characteristics.

Revised adaptive active disturbance rejection sliding mode control strategy for vertical stability of active hydro-pneumatic suspension

The unmanned ground vehicle (UGV) travels in complex and uncertain terrain. Its vertical stability is a key factor affecting the working state and service life of high-sensitivity on-board sensors and mechanical structures. With the development of unmanned platform, a six-wheel independent drive UGV (6WID UGV) came into being. Its complex operating conditions and the unique configuration of active hydro-pneumatic suspension (AHPS) put forward higher requirements for vertical stability control. Based on the AHPS of 6WID UGV, a revised active disturbance rejection sliding mode controller (R-ADRSMC) is designed to improve the vertical stability of UGV. Firstly, the dynamic model of AHPS was established, and a test platform was built to verify the accuracy of the nonlinear characteristics of stiffness and damping. Secondly, an extended state observer (ESO) is used to estimate the disturbance caused by the model’s high nonlinearity and uncertainty. The known disturbance is fed back to ESO to form feedforward compensation, which improves the accuracy of disturbance estimation and compensation. Thirdly, the output of ESO is incorporated into the control law of the sliding mode controller (SMC), giving the control law real-time adaptive capability to the state of suspension system. Finally, the effectiveness of R-ADRSMC and its strong robustness to the uncertainty of road and load parameters are verified by simulation. The results show that compared with passive suspension (PS), active disturbance rejection control (ADRC), and SMC, the proposed R-ADRSMC can effectively improve the vertical stability of UGV under complex road conditions and has better control characteristics.

Damping Control and Experiment on Active Hydro-Pneumatic Suspension of Sprayer Based on Genetic Algorithm Optimization.

High ground clearance self-propelled sprayers usually work in complex road conditions. Due to the large body mass, wide spray boom breath and high center of gravity, the body and spray boom swing sharply during work, which affects operation quality and even endangers safety. This paper proposes a control plan for timely-started active hydro-pneumatic suspension, and designs a fuzzy PID control system based on genetic algorithm optimization. First, MATLAB software is used to simulate and analyze the model, so that the fuzzy PID control optimized by genetic algorithm is obtained. When the sprayer drives on D-grade road, as the speed increases, in comparison between the damping effect of the active suspension and traditional passive suspension, the corresponding root mean square value of vehicle body vibration acceleration decreases by 11.36 and 12.36%, respectively. On the E-grade road surface, with the increase of speed, the corresponding root mean square value of vehicle body vibration acceleration decreases by 13.25 and 14.89%, respectively. Based on indoor bench experiments, the proposed control strategy was verified. Under field road excitation, when the sprayer traveled at 5 km/h, the root mean square acceleration values of the passive and active suspensions were 1.080 and 0.847 m/s2, respectively; when the sprayer traveled at 8 km/h, the root mean square acceleration values of the passive and active suspensions were 1.412 and 1.125 m/s2, respectively, with the root mean square values of vibration acceleration reduced by 21.57 and 20.33%, respectively. Under sand-gravel road condition, when the sprayer traveled at 5 km/h, the root mean square acceleration values of the passive and active suspensions were 1.149 and 0.891 m/s2, respectively; when the sprayer traveled at 8 km/h, the root-mean-square acceleration values of the passive and active suspensions were 1.572 and 1.229 m/s2, respectively, with the root mean square values of vibration acceleration reduced by 22.45 and 21.82%, respectively. During the active control process, the suspension displacement is always kept within the limited range, and as the vehicle speed and road surface level increase, the active suspension has a significantly better damping effect than the passive suspension, which proves effectiveness of the active damping scheme.

Adaptive ride comfort and attitude control of vehicles equipped with active hydro-pneumatic suspension

In this study, an active suspension for combined ride comfort and attitude control of a vehicle equipped with hydro-pneumatic (HP) suspension system is developed. The state-dependent Riccati equation (SDRE) control is employed in the design of the active suspension controller. A detailed sensitivity analysis is performed to examine the effects of the selection of weighting coefficients on the ride comfort and attitude control. According to the results of the sensitivity study, three different sets of fixed weighting coefficients and a fourth set with adaptive weighting coefficients are developed. The adaptive weighting coefficients are implemented by the state constraint in the SDRE formulation. The controller is tuned mainly for ride comfort at low suspension deflections and for keeping the proper vehicle attitude at higher suspension deflections. Simulation results show that the active suspension with the adaptive weighting is successful in improving both ride comfort and the vehicle attitude.

Hierarchical Control Strategy for Active Hydropneumatic Suspension Vehicles Based on Genetic Algorithms

A new hierarchical control strategy for active hydropneumatic suspension systems is proposed. This strategy considers the dynamic characteristics of the actuator. The top hierarchy controller uses a combined control scheme: a genetic algorithm- (GA-) based self-tuning proportional-integral-derivative controller and a fuzzy logic controller. For practical implementations of the proposed control scheme, a GA-based self-learning process is initiated only when the defined performance index of vehicle dynamics exceeds a certain debounce time threshold. The designed control algorithm is implemented on a virtual prototype and cosimulations are performed with different road disturbance inputs. Cosimulation results show that the active hydropneumatic suspension system designed in this study significantly improves riding comfort characteristics of vehicles. The robustness and adaptability of the proposed controller are also examined when the control system is subjected to extremely rough road conditions.

State Dependent Riccati Equation Control of an Active Hydro-Pneumatic Suspension System

In this study, a nonlinear active Hydro-Pneumatic (HP) suspension system is modelled. The HP suspension system model is then incorporated into the quarter car model and a nonlinear controller for the vehicle system is developed. A linear structured model with state dependent matrices of the nonlinear quarter car model is derived for use in controller design. A nonlinear control method, State Dependent Riccati Equation control (SDRE) is used to attenuate sprung mass acceleration, suspension deflection, and tire deflection. The performance of the controller is examined in both frequency and time domains. Active HP suspension system is simulated with sinusoidal inputs at discrete amplitudes and frequencies, and the approximate frequency response functions are obtained. The active HP suspension system is simulated with random road inputs and the root mean square values of the responses are used to evaluate the performance of the controller. The results show that the active suspension successfully and simultaneously decreases the sprung mass acceleration, suspension deflection, and tire deflection around body bounce frequency and thus improved ride comfort and road holding are obtained.

Feedback linearization and sliding mode control for active hydropneumatic suspension of a special-purpose vehicle

Based on modelling and experimental validation of the hydropneumatic spring, a non-linear dynamic model is developed for active hydropneumatic suspensions of a special-purpose vehicle. In order to improve the system response to off-road terrain unevenness and vertical impact force, the non-linear system is transformed into a linear one by means of feedback linearization. Furthermore, a sliding mode control strategy is introduced for the purpose of raising the robustness of the system. The simulation results indicate that the present non-linear controller combining the feedback linearization with the linear control algorithm possesses high control accuracy and strong robustness, and the unique requirements for the special-purpose vehicle are therefore fairly well satisfied.

PID control for active hydropneumatic suspension based on the feedback linearisation

Based on modelling and experimental validation of the hydropneumatic spring, a non-linear dynamic model is developed for the active hydropneumatic suspensions of missile launching vehicle. In order to fulfil the special requirements of mobile launching, the non-linear system is transformed into a linear one by means of feedback linearisation (FBL) according to the theory of differential geometry. Furthermore, a PID control approach is applied for the solution to the system of equations. It is indicated by the simulation results that the present non-linear controller combining the FBL with linear control algorithm is characterised with its fairly simple structure and good performance.

Bandwidth-limited active suspension controller for an off-road vehicle based on co-simulation technology

This paper presents the design process of a controller for bandwidth-limited active hydro-pneumatic suspension employed by an off-road vehicle based on co-simulation technology. First, a detailed multi-body dynamic model of the vehicle is established by using the ADAMS/View software package, which is followed by validation using a vehicle field test. Second, a combined PID and fuzzy controller is designed for the bandwidth-limited active suspension system and then programmed by means of S-functions in Matlab/Simulink, to which a data exchange interface with ADAMS/View is also defined. Third, the proposed control algorithm is implemented on the multi-body dynamic vehicle model to enable the co-simulation to run repeatedly until a more practical controller is achieved. In the end, the proposed active suspension system is compared with a conventional passive system. Simulation results show that the proposed active suspension system considerably improves both the ride and handling performance of the vehicle and therefore increases the maximum traveling speeds even on rough roads.