于海鹏，宋康，谢辉.基于模型预测的电辅助涡轮增压柴油机空气系统优化控制研究[J].内燃机工程,2018,39(4):39-46.
基于模型预测的电辅助涡轮增压柴油机空气系统优化控制研究
Research on Optimal Control of Air System of Diesel Engine with ETurbo Based on Model Prediction
DOI：10.13949/j.cnki.nrjgc.2018.04.007
关键词:电辅助涡轮增压器  柴油机  模型预测控制  自抗扰控制
Key Words:electrically assisted turbocharger(eTurbo)  diesel engine  model predictive control(MPC)  active disturbance rejection control
基金项目:
作者单位
于海鹏，宋康，谢辉 天津大学 内燃机燃烧学国家重点实验室，天津 300072 
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摘要:针对配备电辅助涡轮增压器(electrically assisted turbocharger, eTurbo)和高压废气再循环(exhaust gas recirculation, EGR)的发动机的油耗和电耗最低、进气氧浓度跟踪误差最小等多目标优化问题，提出了一种eTurbo在线优化控制算法：根据目标进气氧浓度和增压压力，采用自抗扰方法调节EGR阀的开度和压气机需求功率；然后采用模型预测控制(model predictive control, MPC)算法，在线将压气机的需求功率分配给涡轮机和电机，以实现发动机油耗、电能消耗和进气氧浓度跟踪误差的最佳折中。在GT SUITE/Simulink平台上的仿真结果表明：在FTP-75驾驶循环下，相比于传统增压柴油机，eTurbo柴油机在该优化算法控制下，增压压力的跟踪误差减小87.20%，进气氧浓度的跟踪误差增加1.93%，发动机等效比油耗改善0.82%，验证了该方法的有效性。
Abstract:An online optimal control algorithm for electrically assisted turbocharger(eTurbo) was proposed for a diesel engine equipped with eTurbo and high pressure exhaust gas recirculation(EGR) to achieve a multi objective optimization: the minimum fuel and power consumptions and the minimum tracking error of intake oxygen concentration. According to the target values of intake oxygen concentration and boost pressure, EGR valve opening and power for compressor were adjusted based on the active disturbance rejection method. The compressor power demand was distributed between turbine and motor based on the model predictive control(MPC) to realize the best trade off among engine fuel consumption, electric consumption, and EGR mass flow. The results of the simulation based on the GT-SUITE/Simulink platform show that under the FTP-75 driving cycle, compared with the traditional turbocharged diesel engine, the boost pressure tracking error of the eTurbo diesel engine is improved by 87.20%, the intake oxygen concentration tracking error increases by 1.93% and the fuel economy is improved by 0.82%, verifying the effectiveness of the proposed optimal control algorithm.
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