Research on Power Characteristic of the Electric Forklift EPS System

He, Yong; Xiao, Biao

doi:10.21307/ijssis-2017-829

Cited by 5 publications

(4 citation statements)

References 18 publications

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“…Both algorithms have a good localization performance. [19] From the analysis of simulation results, the proposed algorithm has better localization precision and computing speed than the SAA. Although the papers were considered only 2D space, but the algorithm could be easily expanded to 3D space.…”

Section: Simulation Results and Analysismentioning

confidence: 98%

See 1 more Smart Citation

PGSA-Based Localization Algorithm for Wireless Sensor Network

Qin

Ying

2016

International Journal on Smart Sensing and Intelligent Systems

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This paper proposes a novel localization algorithm for wireless sensor network (WSN). Accurate localization is very important for WSN. WSN localization problem is sometimes regarded as an optimization problem. Plant growth simulation algorithm (PGSA) is a kind of new intelligent optimization algorithm, which is intelligent simulation of plant growth in natural way. In addition to the common characteristics of intelligent algorithms, PGSA show robustness and provides a global optimal solution, etc. In this paper, further enhancement of the algorithm by adding the plant root of adaptive backlight function to effectively improve the computing speed and localization precision has been reported. Comparing this algorithm with simulated annealing algorithm (SAA), simulation resultsshow that this algorithm has a higher and more consistent localization precision and faster computational speed.

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Section: Simulation Results and Analysismentioning

confidence: 98%

“…Both algorithms have a good localization performance. [19] From Fig.3, PSGA has higher precision than SAA obviously. In fact, by the Equation (6) While, when the blind nodes are distributed intensively, the location error is quite large.…”

Section: )mentioning

confidence: 94%

PGSA-Based Localization Algorithm for Wireless Sensor Network

Qin

Ying

2016

International Journal on Smart Sensing and Intelligent Systems

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“…The practical yaw rate is changing when the forklift steers at a narro w space frequently. If the yaw rate changes too fast, the forklift's handling stability must be influenced directly [30,31]. Thus this paper adds the yaw rate feedback control based on the fuzzy variable transmission ratio control.…”

Section: B the Research Of The Yaw Rate Feedback Control Strategymentioning

confidence: 99%

Research on Variable Transmission Ratio and Yaw Rate Control Strategy of Electric Forklift Steering-by-Wire System

Xiang¹,

Xiao²

2016

IJISA

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Comb ined with the trans mission ratio characteristics of fo rklift steering-by-wire (SBW) system, through the application of fu zzy control technology, the variable trans mission ratio function is designed based on the steering handle angle and vehicle speed, and simu lation analysis of sinusoidal steering is done at low-speed and high-speed. Simu lation results show that the fuzzy variable transmission ratio control can make forklift steering light & sensitive at lo w-speed and steering steady & heavy at high speed, also it can improve the operation stability and reduce the driver's load. Discuss the relationship between yaw rate and forklift handling stability, propose the yaw rate feedback control strategy based on the fuzzy variable t ransmission ratio control, and design a fuzzy self-adaptive PID controller. Simu lation results show that the SBW s ystem based on the fuzzy variable trans mission ratio control with yaw rate feedback can accurately and quickly t rack the desired yaw rate, and reduce or even eliminate the overshoot phenomenon, improve the forklift dynamic performance.

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“…Zhao 18 used a genetic algorithm to optimize the parameters of assist characteristic curve with the minimum actual steering wheel torque and ideal steering wheel torque deviation as the optimization goal. He and Xiao 19 proposed a design method of linear EPS assist characteristic curve considering the influence of speed, steering wheel torque, and load, the assist gain corresponding to different vehicle speeds and loads was obtained by fuzzy rule. In summary, most of the current EPS assist characteristic curve design methods do not reveal the essence of the design, do not systematically consider the driver’s steering intention, and do not consider the chassis dynamics and steering system dynamics separately.…”

Section: Introductionmentioning

confidence: 99%

Study on decomposition and calculation method of EPS assist characteristic curve

Guan

Zhang

Duan

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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Steering feel is closely related to the matching of the EPS assist characteristic curve, however, due to the lack of theoretical basis for the design of the EPS assist characteristic curve, the steering feel can only be changed indirectly by adjusting the magnitude of assist, which is very difficult. To control steering feel directly and reduce the difficulty of adjustment, this paper proposes a decomposition and calculation method of the EPS assist characteristic curve. At first, the mechanism of the EPS assist characteristic curve is revealed. It is found that the process of designing and adjusting the EPS assist characteristic curve is a process of changing the corresponding relationship between the steering wheel torque and the steering motion intensity based on considering vehicle dynamic characteristics. On this basis, the driver’s desired steering motion intensity and the pinion angle position are taken as intermediate variables, the EPS assist characteristic curve is decomposed into three parts: driving style, steady-state inverse characteristics of chassis dynamics, and steady-state inverse characteristics of steering system dynamics. According to the designed driving style and the calibrated steady-state inverse characteristics of chassis dynamics and steering system dynamics, the EPS assist characteristic curve can be directly calculated. The test results show that the EPS system adopting assist characteristic curve calculated can realize the designed driving style and provide consistent and controllable steering feel on the premise of meeting the requirements of steering portability and road feel.

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Research on Power Characteristic of the Electric Forklift EPS System

Cited by 5 publications

References 18 publications

PGSA-Based Localization Algorithm for Wireless Sensor Network

PGSA-Based Localization Algorithm for Wireless Sensor Network

Research on Variable Transmission Ratio and Yaw Rate Control Strategy of Electric Forklift Steering-by-Wire System

Study on decomposition and calculation method of EPS assist characteristic curve

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