装载机系统的智能能源自适应控制
Bingwei Cao1, Changhao Mu1, Jiaqi Dong2
1School of Mechanical and Vehicle Engineering, Changchun University, Changchun 130022, PR China.
ISA transactions
|June 17, 2025
概括
装载机可以通过根据材料类型智能调整弹杆起重来节省能源. 这种能源适应控制 (EAC) 策略可以降低工作阻力,并在除各种材料时提高效率.
科学领域:
- * 机械工程 机械工程
- * 人工智能 * 人工智能
- * 机器人技术 机器人技术
背景情况:
- * 装载机操作面临着不同工作阻力和不可预测的时间变化的因素带来的挑战,导致高能耗.
- *压缩层在开阶段显著影响工作阻力.
- * 现有的控制策略缺乏适应各种工作对象的适应性,阻碍了最佳的能源利用.
研究的目的:
- * 分析压缩层对装载机工作阻力的影响.
- * 为了研究弹杆提升策略对压缩层破坏的影响.
- * 开发一个智能能源适应控制 (EAC) 战略,以优化装载机效率.
主要方法:
- *分析装载机过程,以确定压缩层的影响.
- * 离散元件方法 (DEM) 模拟,以模拟及时提升弹杆的破坏性影响.
- * 开发一种材料识别模型,使用EAC战略中集成的反向传播 (BP) 神经网络算法.
主要成果:
- * 及时提升杆显示了对压缩层的破坏性影响.
- * EAC 策略根据材料类型智能地调整了弹杆起重范围,降低了工作阻力.
- * 峰值发动机功率消耗的显著减少:沙子20.6%,石19.1%,巨石10.9%.
结论:
- * 拟议的EAC战略有效地减少了装载机系统的能源消耗.
- *基于材料类型的弹杆起重范围的智能调整对于能源效率至关重要.
- * 集成BP神经网络和DEM模拟提供了一个强大的方法来优化加载器操作.
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