﻿ 相继增压柴油机调速控制算法研究
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 应用科技  2017, Vol. 44 Issue (5): 30-34  DOI: 10.11991/yykj.201607019 0

### 引用本文

YANG Chuanlei, MA Chuanjie, WANG Yinyan, et al. Research on the speed regulation control algorithms for sequential turbocharging diesel engine[J]. Applied Science and Technology, 2017, 44(5), 30-34. DOI: 10.11991/yykj.201607019.

### 文章历史

Research on the speed regulation control algorithms for sequential turbocharging diesel engine
YANG Chuanlei, MA Chuanjie, WANG Yinyan, HU Song
College of Energy and Power Engineering, Harbin Engineering University, Harbin 150001, China
Abstract: In order to precisely control the speed regulation process of a sequential turbocharging diesel engine, in the joint simulation environment of GT-power and MATLAB/SIMULINK, the speed regulation control models on TBD234V12 sequential turbocharging diesel engine were respectively established on the basis of the classical PID and the fuzzy self-adapted PID(proportion integration differentiation) control algorithm. The simulation and the comparative research were carried out, in addition, the simulative value of the cylinder pressure under the declared working conditions were compared with the testing value, so as to verify the accuracy of the model. The simulation results show that the fuzzy self-adapted PID control algorithm has a better effect than the classical PID algorithm, including fast response, lower overshoot and better control effect.
Key words: diesel engine    sequential turbocharging    speed governing    PID    fuzzy    control    algorithm    simulation

1 控制算法研究 1.1 经典PID控制算法

PID控制器具有结构简单、稳态控制精度高等特点，在控制领域得到广泛应用[10]。PID控制器由比例单元(P)、积分单元(I)和微分单元(D)组成。其输入e(t)与控制量输出u(t)的关系为

 $\mathit{u}\left( \mathit{t} \right){\rm{ = }}{\mathit{K}_{\rm{p}}}\left[{\mathit{e}\left( \mathit{t} \right){\rm{ + }}\frac{1}{{{\mathit{T}_{\rm{I}}}}}\mathit{e}\int {\left( \mathit{t} \right)} {\rm{d}}\mathit{t}{\rm{ + }}{\mathit{T}_{\rm{D}}}\frac{{{\rm{d}}\mathit{e}\left( \mathit{t} \right)}}{{{\rm{d}}\mathit{t}}}} \right]$

1.2 模糊PID控制算法

 图 1 单变量二维模糊控制原理
1.3 模糊自适应PID控制器的设计 1.3.1 确定模糊控制器的结构

 图 2 模糊控制器结构
1.3.2 确定语言变量和语言值得隶属度函数

1.3.3 模糊控制规则的建立

 图 3 输出变量KP、KI、KD的模糊规则视图
1.3.4 输出变量的反模糊化

 ${\mathit{u}^{\rm{*}}}{\rm{ = }}\frac{{\sum\limits_{\mathit{i}{\rm{ = 1}}}^\mathit{k} {\mathit{\mu }{\rm{(}}{\mathit{\mu }_\mathit{i}}{\rm{)}}{\mathit{\mu }_\mathit{i}}} }}{{\sum\limits_{\mathit{i}{\rm{ = 1}}}^\mathit{k} {\mathit{\mu }{\rm{(}}{\mathit{\mu }_\mathit{i}}{\rm{)}}} }}$ (1)

2 相继增压柴油机建模及验证 2.1 相继增压柴油机建模

 图 4 相继增压柴油机GT-power模型
2.2 模型验证

 图 5 气缸压力的仿真值与实验值对比
3 调速控制模型的建立 3.1 建立联合仿真平台

 图 6 联合仿真原理图

 图 7 经典PID控制器仿真模型
 图 8 模糊自适应PID控制器仿真模型
4 仿真结果与分析 4.1 2TC状态突加速情况下调速控制仿真

 图 9 两种PID控制器对阶跃信号的动态响应曲线

4.2 1TC向2TC状态切换过程调速控制仿真

 图 10 两种PID控制器对切换过程的动态响应

5 结论