分布式电推进飞机能量优化动态管理技术研究*

doi:10.11985/2023.03.034

电气工程学报 ›› 2023, Vol. 18 ›› Issue (3): 315-331.doi: 10.11985/2023.03.034

• 新能源发电与电能存储 • 上一篇下一篇

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分布式电推进飞机能量优化动态管理技术研究^*

金贤球¹(), 雷涛¹^,²(), 闵志豪²(), 宋丽娜¹(), 张星雨²(), 张晓斌¹^,²()

1.西北工业大学自动化学院西安 710072
2.西北工业大学飞机电推进技术工业和信息化部重点实验室西安 710072

收稿日期:2022-08-15 修回日期:2023-03-31 出版日期:2023-09-25 发布日期:2023-10-23
作者简介:金贤球，男，1997年生，硕士研究生。主要研究方向为分布式电推进飞机能量管理优化、电推进飞机混合电源系统故障预测和健康管理。E-mail：18007099683@mail.nwpu.edu.cn
雷涛，男，1974年生，博士，副教授。主要研究方向为分布式电推进飞机能量管理优化、飞机电气系统建模仿真、电气系统优化控制、电气系统电能质量分析与检测、故障预测及健康管理。E-mail：lttiger@nwpu.edu.cn
闵志豪，男，1992年生，博士研究生。主要研究方向为电推进飞机电气系统稳定性优化控制、电气系统电能质量分析与检测、电推进飞机能量管理优化和电源系统健康管理。E-mail：minzhihao@outlook.com
宋丽娜，女，2000年生，硕士研究生。主要研究方向为电推进飞机电气系统建模仿真。E-mail：s18182668697@mail.nwpu.edu.cn
张星雨，男，1991年生，博士研究生。主要研究方向为分布式电推进飞机气动系统整体设计。E-mail：jensonzhangbuaa@126.com
张晓斌，男，1963年生，硕士，教授。主要研究方向为先进飞机电气综合控制和负载自动管理系统的技术、飞机供电系统综合实验和测试技术以及飞机电气系统兼容性。E-mail：dg1907@126.com
基金资助:
* 国家自然科学基金资助项目(51877178)

Strategies of Energy Optimal Management for Distributed Hybrid Electrical Propulsion Aircraft

JIN Xianqiu¹(), LEI Tao¹^,²(), MIN Zhihao²(), SONG Lina¹(), ZHANG Xingyu²(), ZHANG Xiaobin¹^,²()

1. School of Automation, Northwestern Polytechnical University, Xi’an 710072
2. Key Laboratory of Aircraft Electric Propulsion Technology, Ministry of Industry and Information Technology of China, Northwestern Polytechnical University, Xi’an 710072

Received:2022-08-15 Revised:2023-03-31 Online:2023-09-25 Published:2023-10-23

摘要/Abstract

摘要：

针对分布式混合涡轮电推进飞机电力系统动态能量管理技术开展研究，将分层模型预测控制(Model predictive control，MPC)算法用于其能量优化控制，针对分布式电推进飞机飞行功率需求的变化特点，采用了两层能量管理控制器的方法。即顶层MPC控制混合电推进飞机系统的飞行过程能量优化分配和多发电机组间、非关键载荷的投切状态等，实现燃油消耗代偿最小的目标，将优化问题等效为混合整形二次规划问题(Mixed integer quadratic programing, MIQP)；底层MPC则控制双向DC-DC变换器，负责管理电池组的充放电状态和维持直流母线的电压动态平衡，利用储能装置的“削峰填谷”，改善并优化系统在飞行任务过程中的平衡工作点，同时实现飞机电网能量的动静态特性的协同控制，达到对混合电推进飞机电力系统的动态能量优化管理的目的，并与采用基于规则控制的能量管理策略进行了对比研究。最后通过建立基于RT-LAB的分布式电推进飞机电力系统硬件在环半实物仿真平台，对混合涡轮电推进飞机的分层MPC能量管理算法进行了技术验证，数字仿真和半物理试验结果表明其对于混合电推进飞机的动态能量管理具有很强的鲁棒性和操作性，验证了理论分析和设计的正确性。

关键词: 分布式混合涡轮电推进飞机, 动态能量管理技术, 分层模型预测控制, 混合整形二次规划(MIQP), 半物理硬件在环仿真

Abstract:

Focusing on dynamic energy management technology of distributed hybrid turbo electric propulsion aircraft power system, the hierarchical model predictive control(MPC) algorithm is used for its energy optimization control, and the two-layer energy management controller method is adopted for the change characteristics of flight power demand of distributed electric propulsion aircraft. That is, the top-level MPC controls the optimal distribution of energy during flight of the hybrid electric propulsion aircraft system and the switching state of multi-generator sets and non-critical loads, etc., to achieve the goal of minimizing fuel consumption compensation, and equivalently the optimization problem as the mixed integer quadratic programming problem(MIQP). The underlying MPC controls the bidirectional DC-DC converter, which is responsible for managing the charge and discharge state of the battery pack and maintaining the voltage dynamic balance of the DC bus, using the “peak shaving and valley filling” of the energy storage device to improve and optimize the balance working point of the system during the flight mission, and at the same time realize the collaborative control of the dynamic and static characteristics of the aircraft power grid energy, so as to achieve the purpose of dynamic energy optimization management of the hybrid electric propulsion aircraft power system, and compare with the energy management strategy using rule-based control. Finally, by establishing a distributed electric propulsion aircraft power system hardware-in-the-loop semi-physical simulation platform based on RT-LAB, the layered MPC energy management algorithm of hybrid turbine electric propulsion aircraft is technically verified, and the digital simulation and semi-physical experimental results show that it has strong robustness and operability for dynamic energy management of hybrid electric propulsion aircraft, which verifies the correctness of theoretical analysis and design.

Key words: Distributed hybrid electrical propulsion aircraft, dynamic energy management technology, hierarchical model predictive control, mixed integer quadratic programing, hard-in-loop test bench

中图分类号:

V11
TP13

金贤球, 雷涛, 闵志豪, 宋丽娜, 张星雨, 张晓斌. 分布式电推进飞机能量优化动态管理技术研究^*[J]. 电气工程学报, 2023, 18(3): 315-331.

JIN Xianqiu, LEI Tao, MIN Zhihao, SONG Lina, ZHANG Xingyu, ZHANG Xiaobin. Strategies of Energy Optimal Management for Distributed Hybrid Electrical Propulsion Aircraft[J]. Journal of Electrical Engineering, 2023, 18(3): 315-331.

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设计参数	参考值	设计参数	参考值
推进电机数量	2(主)+4(辅)	能源组成	油电混合
翼展面积/m²	15	机体空重/kg	750
巡航高度/m	300~700	最大巡航速度/(km/h)	260
飞行时长/h	0.5~1	航程/km	100~300
爬升速率/(m/min)	350	有效载荷/kg	<300
推进系统功率/kW	80~120	其他电功率/kW	30~70
发电机容量/kW	150~200	电池组容量/(A·h)	0~100

性能参数	数值	性能参数	数值
任务时长/h	1	平均功率/kW	150
总能量需求/MJ	约60	峰值功率/kW	200
发电机额定功率/(kV·A)	140	燃油量/L	7
电池组额定电压/V	90	电池组容量/(A·h)	70

状态	发电机G1	发电机G2	电池组	负载功率等级
状态1	0	0	1	极低
状态2	1	0	0	较低
状态3	1	0	1	一般
状态4	1	1	0	较高
状态5	1	1	1	极高

分布式电推进飞机能量优化动态管理技术研究^*

Strategies of Energy Optimal Management for Distributed Hybrid Electrical Propulsion Aircraft

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