SIA OpenIR  > 工业信息学研究室
面向能源管理的非侵入式电机效率估计方法研究
其他题名Research on Nonintrusive Efficiency Estimation Method for the Energy Management
于洪霞1,2
导师胡静涛
分类号TM3
关键词电机 能源管理 效率估计 等效电路 Ekf
索取号TM3/Y74/2011
页数127页
学位专业机械电子工程
学位名称博士
2011-11-25
学位授予单位中国科学院沈阳自动化研究所
学位授予地点沈阳
作者部门工业信息学研究室
摘要电机作为各种设备的驱动力,广泛应用于工业、农业、商业以及公用设施等各个领域。从全球范围看,电机系统的用电量平均占世界总用电量的50%以上、占工业用电量的70%左右。在目前能源紧张、能源价格不断上涨的情况下,实现电机系统节能对国家和企业意义重大。 电机系统的节能应该从降低电机的生命周期费用来考虑。电机消耗的电能费用占电机生命周期费用很大部分,降低电机消耗电能费用的有效方式之一是电机能源管理,电机效率估计是电机能源管理中的关键技术之一。本文依托863课题“大型联合企业先进能源管理系统开发”( 2008AA042901),围绕电机非侵入式效率估计问题,进行了如下几方面研究: (1)基于等效电路和铁损约束的电机效率估计。针对现有等效电路法效率估计精度低、稳定性差的问题,提出了一种基于测量数据和铁损约束的电机效率估计方法。首先,基于包含杂散损耗等效电阻的等效电路,研究了基于双负载点测量数据的效率估计方法,在此基础分析出了效率估误差的原因;其次,利用电机铁损是不变的且在一定经验范围内的特点,提出了基于双负载点测量数据和铁损约束的效率估计方法,建立了基于双负载点测量数据和铁损约束的参数辨识优化模型;最后对单负载点运行的电机,建立了基于单负载点测量数据和铁损约束的参数辨识优化模型;实验结果表明,所提方法显著提高了效率估计的精度。 (2)基于转速和负载转矩同时估计的非侵入式效率估计。针对现有效率估计方法用到损耗近似值的问题,考虑计算电机输出功率最直接的方式就是用电机的转速和负载转矩计算,提出了一种同时直接估计异步电机转速和负载转矩,实现电机非侵入式效率估计的方法。首先建立了包含转速和负载转矩的电机增广数学模型;其次,基于该模型用EKF实现了电机转速和负载转矩的同时估计;最后,用估计出的转速和负载转矩的稳态均值计算出电机的效率;实验结果表明,所提方法以较高的精度实现了电机的非侵入式效率估计。 (3)基于改进EKF的电机非侵入式效率估计。针对EKF法估计结果受选择的噪声协方差阵影响较大的问题,提出了两个改进方法。首先,提出了噪声协方差阵智能优化法,基于转速和负载转矩的估计值和测量值,建立了优化模型,用PSO算法对优化模型求解,改变了试凑法获得噪声协方差阵的繁琐过程,实验结果表明,优化后的噪声协方差阵提高了效率估计的精度。其次,提出了噪声协方差阵自适应估计法,运用Sage-Husa自适应滤波算法,结合EKF算法,实现了噪声协方差阵自适应估计,实验结果表明,该法的估计结果受选择的噪声协方差阵初值影响较小,且以较高的精度估计出了电机效率。 (4)效率估计在电机能源管理中的应用。首先,针对现有电机投资回收期分析模型,没有考虑同一负载被不同电机拖动需要的输出功率是不同的这一事实,对电机的投资回收期分析模型进行了改进;其次为了评估新电机非额定负载点能效,建立了基于电机铭牌和损耗约束的参数辨识优化模型;最后基于现有电机的效率估计结果和新电机在该负载点的能效评估,对不同类型的负载分别给出了简单投资回收期和综合投资回收期的比较。
其他摘要Electric motors have been widely used in industry, business, public service and household electrical appliances etc fields. Statistics indicate that the electric motors are generally responsible for about 2/3 of industrial power consumption in worldwide, or about 50% of overall power consumption. As the global energy shortage and energy prices rising, energy saving in the motor system has great significance for the state and enterprises. Energy saving in the motor system should be considered from reducing the motor's life cycle cost. The energy costs account for most of the life cycle cost, energy management is an effective way to reduce the energy cost, efficiency estimation is one of the key technique in energy management. With the support of 863 subjects "Advanced energy management system of conglomerate development" (2008AA042901), this thesis carried out the following four aspects research around the motor efficiency estimation problem: (1) The motor efficiency estimation based on equivalent circuit and core loss constraints was researched. For overcoming the shortcoming that the estimation results of the efficiency estimation method using only measured data was not stable and accurate, a new efficiency estimation method was presented basing on the measured data and core loss constraints. First, using the equivalent circuit including equivalent stray loss resistance, the efficiency estimation method using measured data at double load point was researched, and the efficiency estimation error was analyzed. Secondly, use of the characteristics that motor iron loss is constant and in a certain experience range, a parameter identification optimization model using double load point measured data and core loss constraints was established. Finally, for single load point running motor, a parameter identification optimization model using the one load point data and core loss constraints was established. The experimental results show that accuracy of the efficiency estimation was significantly improves after adding iron loss constraint to optimization model. (2) The non-intrusive efficiency estimation through estimating speed and load torque simultaneously was researched. For overcoming the shortcoming that loss approximation was used in the current efficiency estimation method, and Considering the most direct way of calculating the motor output power is to use the motor speed and load torque calculation, an nonintrusive efficiency estimation method by estimating directly speed and load torque was presented. First, an augmented model of motor including the speed and load torque was established; Secondly, the speed and load torque were estimated simultaneously by EKF based on the model; Next, the efficiency was computed using the steady-state mean of estimated speed and load torque, the nonintrusive efficiency estimation was implemented. Experimental results show that the proposed method achieve high precision non-invasive motor efficiency estimation. (3) The non-intrusive motor efficiency estimation basing on improved EKF was researched. The two improving method were presented to overcome the shortcoming that the estimation results of EKF was affected greatly by the noise covariance. First, an intelligent optimization method of noise covariance was proposed, an optimal model using estimated and measured speed and load torque value was established, then the optimal model was solved using PSO, the tedious process of trial and error method was improved, experimental results show that the efficiency estimation accuracy was improved using optimized noise covariance matrix in EKF method. Secondly, a method of noise covariance matrix adaptive estimation was proposed; the noise covariance matrix was estimated adaptively by combining the Sage-Husa adaptive filter and EKF algorithm, experimental results show that the estimation results were affected seldom by the selected initial value of noise covariance matrix, and have high accuracy. (4) The problem of applying estimated motor efficiency in energy management was researched. First, considering the current payback period analysis model without considering the desired output power of the same load dragged by different motor is different, a modified model of the payback period analysis was given; Secondly, to evaluate the energy efficiency of non-rated load, a parameter identification optimization model based on the motor nameplate and the loss constraints was established, Finally, a simple payback period and comprehensive payback period of investment for different load type are given by the efficiency estimation value of existing and new motor.
语种中文
产权排序1
文献类型学位论文
条目标识符http://ir.sia.cn/handle/173321/9362
专题工业信息学研究室
作者单位1.中国科学院沈阳自动化研究所
2.中国科学院研究生院
推荐引用方式
GB/T 7714
于洪霞. 面向能源管理的非侵入式电机效率估计方法研究[D]. 沈阳. 中国科学院沈阳自动化研究所,2011.
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