Real-time implementation of an online Model Predictive Control for IPMSM using parallel computing on FPGA

Real-time implementation of an online Model Predictive Control for IPMSM using parallel computing on FPGA
复制标题

使用 FPGA 上的并行计算实时实现 IPMSM 在线模型预测控制

DOI:
10.1109/ipec.2014.6869605
复制
发表时间:
2014
期刊:
2014 International Power Electronics Conference (IPEC-Hiroshima 2014 - ECCE ASIA)
影响因子:
--
通讯作者:
Böcker
Böcker
中科院分区:
--
文献类型:
--
作者:
Böcker

文献摘要

参考文献

被引文献

相似文献

与传统控制方法相比,模型预测控制(MPC)具有许多优点。MPC的问题是计算成本高,控制周期长。这使得MPC对于时间常数较小的过程不具吸引力,例如用于电动汽车的带内磁体的永磁同步电机(IPMSM)。本文针对具有固有输出饱和的非线性系统,提出了一种模型预测控制方法。这种方法为在线MPC提供了实时能力,即使对于时间常数在毫秒范围内的过程也是如此。通过由现场可编程门阵列(现场可编程门阵列)提供的并行计算的可能性,这变得可行。这可以克服计算量大的缺点。在介绍了这种实时预测控制方法的工作原理后,通过仿真验证了该方法的性能,并通过在试验台上对一台车用IPMSM的测试结果验证了该方法的实时性。
Model Predictive Control (MPC) offers a variety of advantages compared to conventional control methods. The problem with MPC is the high computational cost and the associated long control cycle time. This makes MPC unattractive for processes with small time constants, as in permanent magnet synchronous motors with interior magnets (IPMSM) for electric vehicles. In this paper a Model Predictive Control method for nonlinear systems with inherent output saturation is presented. This approach offers real-time capability for online MPC even for processes with time constants in the millisecond range. This becomes feasible by the possibility of parallel computation, as provided by a FPGA (Field Programmable Gate Array). This can overcome the drawbacks of the high computational effort. After the functional principle of this real-time MPC approach is presented, the resulting performance is shown by simulation results and the real-time capability is verified by test results of an IPMSM for automotive applications on a testbench.
FPGA 控制平台上感应电机驱动器的动态可重构控制结构
DOI: 10.1080/09398368.2010.11463745
发表时间: 2010
期刊: EPE Journal
影响因子: 0.5
作者:
S. Mathapati;J. Böcker
通讯作者: J. Böcker
使用 FPGA 上并行计算的 IPMSM 快速在线模型预测控制
DOI: --
发表时间: 2013
期刊: International Electric Machines and Drives Conference
影响因子: --
作者:
Michael Leuer;J. Bocker
通讯作者: J. Bocker
IPMSM 的效率优化模型预测扭矩控制
DOI: 10.1109/energycon.2014.6850398
发表时间: 2014
期刊: 2014 IEEE International Energy Conference (ENERGYCON)
影响因子: --
作者:
Rüting;Böcker
通讯作者: Böcker