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- Title
Braking Intention Identification Strategy of Electric Loader Based on Fuzzy Control.
- Authors
Ye, Yueying; Wu, Xia; Lin, Tianliang
- Abstract
Featured Application: The proposed braking intention identification control strategy has braking stability. As a widely-used construction machinery, the electric loader has the potential to recover braking energy due to its large mass and frequent starts and stops. Identifying braking intention accurately is the foundation of braking energy recovery. The typical braking condition of an electric loader is analyzed; the braking intention is divided into sliding brake, mild braking, moderate braking, and emergency braking. A large number of braking data were collected under different braking intentions, which are used as the basis for fuzzy control variable partitioning, fuzzy controller parameter setting and fuzzy control rule formulation. The control strategies of deceleration intention identification based on accelerator pedal, braking intention identification based on brake pedal and sliding brake intention identification are proposed in this paper, respectively. This paper takes the hydraulic brake pressure as a feedback parameter, even if there is hysteresis or failure based on the intention of pedal identification, the system can still provide sufficient braking strength to ensure the braking safety. The AMESim(R12)-Matlab/Simulink co-simulation model and prototype are built to verify the feasibility of the control strategy under different braking intention identification. The results show that the braking strength under stronger braking intention can satisfy the braking demand whether at a speed of 2 m/s or 12 m/s, which ensures the safety of emergency braking, and the electric loader can provide stable braking strength under different braking intention and different speed. This has good braking stability.
- Subjects
HYDRAULIC brakes; INTENTION; BRAKE systems; CONSTRUCTION equipment; FUZZY sets; ELECTRIC machinery; AUTOMOBILE brakes; ANTILOCK brake systems in automobiles
- Publication
Applied Sciences (2076-3417), 2023, Vol 13, Issue 20, p11547
- ISSN
2076-3417
- Publication type
Article
- DOI
10.3390/app132011547