凌健，谢辉.共轨柴油机基于瞬时轨压波形特征参数的喷油量观测方法[J].内燃机工程,2017,38(1):61-69.
共轨柴油机基于瞬时轨压波形特征参数的喷油量观测方法
Observation of Fuel Injection Quantity Based on Characteristic Parameters of Instantaneous Rail Pressure Waveforms for Common Rail Diesel Engines
DOI：
关键词:内燃机  柴油机  高压共轨  轨压  特征参数  喷油量观测
Key Words:IC engine  diesel engine  high pressure common rail  rail pressure  characteristic parameter  fuel injection quantity observation
基金项目:国家“八六三”高技术研究发展计划项目（2012AA111706）；国家自然科学基金项目（51307119）
作者单位
凌健，谢辉 天津大学 内燃机燃烧学国家重点实验室，天津 300072 
摘要点击次数: 2016
全文下载次数: 1844
摘要:为了揭示柴油机高压共轨燃油喷射系统中瞬时轨压波动规律及其特征参数与喷油量的关系，提出了一种基于瞬时轨压波形特征参数的喷油量观测方法。将瞬时轨压波形划分成一系列典型片段，采用4个特征点和4个特征段来描述每缸瞬时轨压波动特征，并用10个特征参数来评价每缸喷油过程的瞬时轨压波动特征。对各稳态试验工况点瞬时轨压波动特征参数均值化处理后，建立了轨压波形群特征数据库，并揭示了不同工况下瞬时轨压波动规律。基于燃油连续性方程，构建了喷油量观测模型，利用轨压波形群特征数据库对喷油量观测模型进行参数辨识和离线验证。结果表明：该喷油量观测模型结构简单，观测精度高，为在电控单元中的应用奠定了基础。
Abstract:To precisely reveal the relation between fuel injection quantity and characteristic parameters defined from the fluctuation law of instantaneous rail pressure of high pressure common rail fuel injection system of diesel engines， a fuel injection quantity observation （IQO） method was proposed based on the characteristic parameters of instantaneous rail pressure waveforms. With this method， the instantaneous rail pressure waveforms were divided into a series of typical segments. Four characteristic points and four characteristic segments were defined to describe the instantaneous rail pressure fluctuation characteristics of each cylinder. And ten characteristic parameters were defined to evaluate the instantaneous rail pressure fluctuation characteristics in the fuel injection process of each cylinder. A database of the characteristics of rail pressure waveform groups was set up and the fluctuation law of the instantaneous rail pressure under different operating conditions was revealed by mean processing of the characteristic parameters of the instantaneous rail pressure fluctuation at every steady experimental operating point. An IQO model was established by the fuel continuity equations， and calibrated by the parameter identification and offline validation with the characteristics database of rail pressure waveform groups. The results show that the IQO model has simple structure and high observation accuracy and it lays a good foundation for further engineering application in electronic control unit （ECU）.
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