Throttling Loss Energy-Regeneration System Based on Pressure Difference Pump Control for Electric Forklifts

带宽遏流 节气门 汽车工程 控制理论(社会学) 转速 电子速度控制 背压 能量(信号处理) 工程类 计算机科学 机械工程 控制(管理) 电气工程 数学 统计 人工智能 气体压缩机
作者
Yuanzheng Lin,Tianliang Lin,Zhihong Li,Haoling Ren,Qihuai Chen,Junyi Chen
出处
期刊:Processes [Multidisciplinary Digital Publishing Institute]
卷期号:11 (8): 2459-2459 被引量:2
标识
DOI:10.3390/pr11082459
摘要

At present, the hydraulic systems of electric forklifts and traditional internal combustion forklifts are mostly valve-controlled speed-regulation systems, which have large throttling losses and potential energy waste. To further improve the energy-saving ability of electric forklifts, the forklift’s common working conditions are analyzed in this paper. A throttling loss energy-regeneration system based on pressure difference pump control is designed, and the system’s working principle is described. Aiming to deal with the problem that the pump−valve compound speed regulation with constant pressure difference could not realize high controllability and energy saving at the same time, a control strategy for variable pressure difference pump−valve compound speed regulation based on pressure balance control is proposed. The handle signal is positively related to the target speed of the oil cylinder. In the low-speed stage, the closed-loop control of the actual output torque of the motor/generator keeps the pressure difference across the proportional throttle valve unchanged, and the speed adjustment is realized by changing the opening of the proportional throttle valve. In the high-speed stage, the valve opening area is kept unchanged and the target pressure difference is changed to achieve the target speed. Finally, the feasibility of the control strategy is verified through an AMESim simulation, and the minimum pressure difference switching point is determined through experiments. The experiments show that the system’s energy-saving efficiency can reach 21.5% under a 1 t load. With the increase in the load, the system’s energy-saving efficiency can be further improved.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
华仔应助科研通管家采纳,获得10
刚刚
科研通AI2S应助科研通管家采纳,获得10
刚刚
SYLH应助科研通管家采纳,获得10
刚刚
CipherSage应助科研通管家采纳,获得10
刚刚
刚刚
SciGPT应助科研通管家采纳,获得10
刚刚
阿金完成签到,获得积分20
1秒前
在水一方应助清欢采纳,获得10
1秒前
1秒前
赘婿应助科研通管家采纳,获得10
1秒前
干净莆应助科研通管家采纳,获得10
1秒前
圣晟胜发布了新的文献求助10
1秒前
2秒前
jiangnan发布了新的文献求助10
2秒前
范先生发布了新的文献求助10
2秒前
shiyuan发布了新的文献求助10
3秒前
Jane完成签到,获得积分10
3秒前
yixuebing完成签到,获得积分20
3秒前
万重山完成签到,获得积分10
4秒前
Godnian发布了新的文献求助10
4秒前
4秒前
叶123发布了新的文献求助10
5秒前
张雯琪完成签到,获得积分10
5秒前
善学以致用应助pppy采纳,获得10
5秒前
5秒前
yuemeichi完成签到,获得积分10
5秒前
S-Lab Sonic发布了新的文献求助10
5秒前
huifang发布了新的文献求助10
5秒前
是小曹啊发布了新的文献求助10
5秒前
liu完成签到,获得积分10
6秒前
张慧仪发布了新的文献求助10
6秒前
开心不评完成签到,获得积分10
6秒前
7秒前
七言完成签到,获得积分10
7秒前
噜噜噜完成签到,获得积分10
7秒前
情怀应助李小伟采纳,获得10
7秒前
猪猪完成签到,获得积分10
8秒前
默默平文完成签到,获得积分10
9秒前
9秒前
高分求助中
Thinking Small and Large 500
Algorithmic Mathematics in Machine Learning 500
Handbook of Innovations in Political Psychology 400
Mapping the Stars: Celebrity, Metonymy, and the Networked Politics of Identity 400
《续天台宗全书•史传1--天台大师传注释类》 300
Visceral obesity is associated with clinical and inflammatory features of asthma: A prospective cohort study 300
Getting Published in SSCI Journals: 200+ Questions and Answers for Absolute Beginners 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3838908
求助须知:如何正确求助?哪些是违规求助? 3381351
关于积分的说明 10517883
捐赠科研通 3100836
什么是DOI,文献DOI怎么找? 1707788
邀请新用户注册赠送积分活动 821920
科研通“疑难数据库(出版商)”最低求助积分说明 773048