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Rail Pressure Estimation for Fault Diagnosis in High Pressure Fuel Supply and Injection System

机译:高压燃料供应和注射系统故障诊断的轨道压力估计

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Engine roughness (ER) is a complex issue in GDI engines and a frequent customer complaint in workshops. Still it is hard to isolate the root cause of the vibration which is received by the driver. The present paper aims to identify the type and extent of faults causing ER that have their origin in the fuel supply and injection system. The method is presented using the injectors as an example, since they have a great impact on engine related vibrations. The injectors affect ER through mixture formation. For example, a deviating amount of injected fuel mass on one cylinder leads to a deviating delivery of work during the combustion cycle and thus causes vibrations. For the investigation additional pressure sensors were installed in the high pressure fuel system to observe the transfer behavior in the hydraulic system. Tests were executed in different reference and fault states, where a fault state is represented by deviating mass flows of an injector. The generated data is used to develop a parameter estimation model, describing the pressure in the fuel rail of the investigated engine. Firstly, a set of reference parameters is generated by a parameter optimization algorithm for each operating point under reference conditions. Then, these sets of parameters are used for initial calibration of the model for the following injector diagnosis. Observing the adaptation of a separate set of diagnostic parameters, allows for a precise pinpointing to a defective injector. It also delivers information about the type of fault and its size. Finally, the results are reconfirmed by executing the diagnosis on data of a healthy system to preclude mis-detections of faults.
机译:发动机粗糙度(ER)是GDI发动机的复杂问题以及常客投诉的研讨会。仍然很难隔离驾驶员接收的振动的根本原因。本文旨在识别导致燃料供应和注射系统中的原点的误差的类型和程度。使用喷射器作为示例呈现该方法,因为它们对发动机相关振动产生很大影响。注射器通过混合物形成影响ER。例如,在一个汽缸上的注射燃料质量的偏差量导致在燃烧循环期间偏离工作的递送,从而导致振动。对于调查,额外的压力传感器安装在高压燃料系统中,以观察液压系统中的转移行为。在不同的参考和故障状态下执行测试,其中通过偏离喷射器的质量流来表示故障状态。所生成的数据用于开发参数估计模型,描述所研究的发动机的燃料轨道中的压力。首先,通过参考条件下的每个操作点的参数优化算法生成一组参考参数。然后,这些参数集用于以下注射器诊断的模型的初始校准。观察单独的诊断参数集的适应,允许精确定位到有缺陷的注​​射器。它还提供有关故障类型及其大小的信息。最后,通过执行健康系统数据的诊断来重新确认结果,以排除错误检测故障。

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