谢辉，李梦觉，宋康.基于负载转矩主动观测的农用柴油机瞬态过程控制研究[J].内燃机工程,2020,41(3):72-80.
基于负载转矩主动观测的农用柴油机瞬态过程控制研究
Study on Transient Control of an Agricultural Diesel Engine Based on Load Torque Active Observation
DOI：10.13949/j.cnki.nrjgc.2020.03.010
关键词:柴油机  涡轮增压  转矩控制  自学习  主动抗扰控制
Key Words:diesel engine  turbo charge  torque control  self learning  active disturbance rejection control
基金项目:国家自然科学基金项目（51906174）
作者单位
谢辉，李梦觉，宋康 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:针对农用柴油机在瞬态突加负载工况下因涡轮迟滞效应造成的发动机转速下降和油耗上升问题，提出一种基于负载转矩主动观测的农用柴油机瞬态过程控制算法。首先，建立了农耕机耕地阻力矩和发动机驱动转矩预测模型，采用跟踪微分器实现了作业模式识别、耕深预测及负载转矩预测，设计了增压压力前馈控制器；然后将预测模型的偏差与外部转矩干扰统一视为“总扰动”，采用扩张状态观测器进行在线估计和补偿；接着基于耕深与发动机转速的动态过程信息，采用递推优化算法设计了负载转矩模型的参数学习算法，用于在线优化模型参数，提高前馈精度，降低总扰动观测负担。在试验校准的高精度Simulink平台上，对算法进行仿真验证，结果表明：较传统控制方法，采用该控制方案后，瞬态过程的空气供给速度提升53.1%，指示转矩响应速度提升44.7%，进而使发动机的转速波动降低98.8%，瞬态过程有效燃油消耗率降低7.0%。
Abstract:In view of the problems of reduced speed and increased fuel consumption under transient sudden load conditions due to turbo lag effect, a transient control algorithm for an agricultural diesel engine based on load torque active observation was proposed. First of all, a prediction model of agricultural machine arable land resistance and engine brake torque was established. By adopting a tracking differentiator to implement the operation mode recognition, as well as the prediction of plough depth and load torque, a boost pressure feedforward controller was designed. Secondly, under the premise that the deviation of the prediction model and the external torque disturbance were regarded as “total disturbance”, an expanded state observer was used for online estimation and compensation. Then, based on the dynamic information of plough depth and engine speed, a parameter self-learning scheme for the load torque model was designed using a recursive optimization algorithm to improve feedforward accuracy, and reduce the observation burden of total disturbance. Finally, the algorithm was verified on a calibrated high-precision SIMULINK simulation platform. Results show that compared with traditional control method, this algorithm can increase the transient air supply speed by 53.1%, and accelerate the indicated torque response by 44.7%, thus reducing the engine speed fluctuation by 98.8%, and the transient fuel consumption by 7.0%.
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