Study on Anti-Rollover of the Counterbalance Forklift Based on Extension Hierarchical Control

Xia Guang,Li Jiacheng,Tang Xiwen,Zhao Linfeng,Sun Baoqun 한국자동차공학회 2021 International journal of automotive technology Vol.22 No.3

The anti-rollover control actuator of a counterbalance forklift is determined by analysing its structural characteristics and roll-over mechanism. An anti-rollover control strategy for counterbalance forklifts based on extension decision is proposed, and the anti-rollover extension hierarchical controller, including the upper-layer extension and lower-layer execution controls, is designed. The upper-layer extension controller divides the forklift anti-rollover control domain into three types, namely, classical domain, extension domain and non-domain, and determines the weight coefficient of the lower layer execution controller. The lower-layer execution controller receives the weight coefficient determined by the upper-layer extension controller, controls the weight distribution on the yaw rate and lateral acceleration controllers and executes the command to obtain the anti-rollover extension control of the counterbalance forklift. The European standard condition simulation and real vehicle test results show that the anti-rollover control strategy of the counterbalance forklift based on the extension decision can effectively reduce the forklift roll range under high-speed emergency steering conditions, prevent the forklift from rolling over and improve the stability and active safety of the counterbalance forklift.

Anti-rollover of the counterbalanced forklift truck based on model predictive control

Guang Xia,Jiacheng Li,Xiwen Tang,Yang Zhang,Jinfang Hu 대한기계학회 2021 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.35 No.5

To reduce the probability of a rollover accident of a forklift during high-speed steering, a hydraulic support cylinder is designed as an actuator to provide lateral support for the forklift. Aiming at the problem of judging the safety domain in the process of forklift driving, this paper proposes a strategy for dividing the forklift’s driving state on the basis of the zero moment point. The relationship between the zero moment point’s lateral component and the forklift’s support plane is used as the basis for division. The forklift rollover process is divided into a safe stage, a controllable danger stage, and a critical rollover stage. In the safe stage, the cylinder does not provide support force, and in the controllable danger stage, the cylinder support force is adjusted on the basis of the model predictive control algorithm to adjust the forklift. The cylinder can be controlled to provide maximum support for the body during the critical rollover phase. This method takes the three-degrees-of-freedom forklift anti-rollover model as the control object and serves as the basis for the calculation of the zero moment point. The anti-rollover controller is built in MATLAB/Simulink to simulate the European standard operating conditions and to verify the actual vehicle test. Results show that the predictive control of the forklift anti-rollover model based on the zero moment point can effectively improve the body attitude of the forklift during high-speed steering and prevent the forklift from rolling over.

CONTROL STRATEGY FOR SHIFT SCHEDULE CORRECTION BASED ON DRIVING HABITS FOR VEHICLES WITH AUTOMATIC TRANSMISSION

Guang Xia,Jun Gao,Xiwen Tang,Shaojie Wang,Baoqun Sun 한국자동차공학회 2020 International journal of automotive technology Vol.21 No.2

A shift schedule modification program is an intelligent system for automatic transmission. This program can adjust shift points to cater to drivers with different driving habits. An important prerequisite in designing a personalized shift schedule is identifying the driving habits of drivers. In this study, we developed an identification algorithm based on wavelet neural network and Bayesian fusion decision-making. First, a system for identifying driving styles was established based on the wavelet neural network. Second, the results were integrated by Bayesian fusion decision-making to obtain the driving habits. Finally, different correction coefficients were selected based on driving habits to satisfy the requirements of drivers. Experimental results show that the driving habits can be accurately identified based on wavelet neural network and Bayesian fusion decision-making, and the correction control strategy can rectify the shift schedule effectively. The correction control strategy satisfies the requirements of different drivers for vehicle performance and enhances the intelligence of automatic transmission.

Anti-Rollover Control Based on Stable Zone Partition of Counterbalanced Forklift Trucks

Xia Guang,Xia Yan,Tang Xiwen,Zhao Linfeng,Hu Jinfang 한국자동차공학회 2021 International journal of automotive technology Vol.22 No.6

To improve the anti-rollover capacity of a counterbalanced forklift, a two-stage rollover dynamic model is established on the basis of the forklift structure. Stable zones are divided according to the two-stage lateral load transfer rate: stable region, relatively stable region, dangerous zone and abnormal dangerous zone. An anti-rollover layered control strategy based on stable zone partition is proposed, and different anti-rollover control actuators are selected: dynamic balance weight, anti-rollover cylinder and steering cylinder. Anti-rollover controllers consist of the upper stable region identification controller, the middle-level controller based on model predictive control (MPC) and the lower layer executive controller. The upper stable region identification controller performs stable zone recognition based on the two-stage lateral load transfer rate. The middlelevel MPC controller calculates the required control torque with the body’s lateral angle and yaw rate as the control objectives. The lower layer executive controller controls the balance weight, anti-rollover cylinder and the steering cylinder according to the improved chain incremental allocation method to meet the target control torque. Simulation and real vehicle tests based on MATLAB/Simulink show that the anti-rollover control based on stable zone partition can greatly reduce the risk of forklift rollover and improve the forklift safety.

Adaptive Fault-Tolerant Control Considering the Actuator Failure of Forklift Anti-Rollover System

Xia Guang,Li Tao,Tang Xiwen,Zhang Yang,Zhao Linfeng 한국자동차공학회 2023 International journal of automotive technology Vol.24 No.3

An adaptive fault-tolerant anti-rollover fuzzy system is proposed to improve the anti-rollover performance of counterbalanced forklifts. Considering the actual control input, various unpredictable actuator failure models in the system are established. Based on the three degree-of-freedom (DOF) model of a counterbalanced forklift, an anti-rollover Takagi-Sugeno (T-S) fuzzy system is established. The stability of this anti-rollover system is analyzed to ensure its stability under specific control inputs and external disturbances. When the upper limits of actuator faults and disturbances are unknown, an adaptive fault-tolerant control method is designed to update the controller parameters. The sufficient conditions for the stability of the forklift anti-rollover system in the presence of actuator faults and external disturbances are given using the Lyapunov stability theory. Simulation and real vehicle tests based on MATLAB/Simulink show that the anti-rollover system with adaptive fault-tolerant control can reduce impacts effectively and quickly after the actuator fails, thereby improving the safety and reliability of the forklift.

Center of Gravity Position Estimation of Counterbalanced Forklift Truck Based on Multi Model Data Fusion

Xia Guang,Zhang Chenhao,Tang Xiwen,Zhang Yang,Zhao Linfeng 한국자동차공학회 2023 International journal of automotive technology Vol.24 No.5

The center of gravity of a forklift truck, a crucial parameter for vehicle stability, changes with different loads during operation. We propose an estimation algorithm for the center of gravity position suitable for a counterbalanced forklift truck. By installing sensors on the fork, we use an inclinable platform and propose a static joint center of gravity measurement method. For straight-line driving, we establish a longitudinal dynamics model and propose a nonlinear H∞ estimation algorithm. For steering conditions, we establish a roll dynamics model and propose a forgetting factor recursive least square estimation algorithm. A data fusion algorithm for the forklift truck’s center of gravity position under various working conditions is proposed. The fusion of these estimation results yields the best estimated center of gravity height. We validate the algorithm’s effectiveness using a hardware-in-the-loop simulation platform under different working conditions. The experiments demonstrate the algorithm’s fast parameter fitting, wide applicability, and accurate position control within a 5 % error range.