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Indirect Adaptive Closed-Loop Control of Solenoid Actuated Gas and Liquid Injection Valves

机译:螺线管驱动气体和液体注入阀的间接自适应闭环控制

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Solenoid-actuated injection valves are typically driven open loop by a predetermined voltage or current profile. There is unit-to-unit variation of the valve electromagnetic/mechanical parameters as well as electrical supply transients, flow force transients and operating conditions while the drive voltage or current profile is fixed. Hence, by definition open-loop drive is suboptimal. Extensive on engine calibration is necessary to correlate the movement of the armature to the current profile in the solenoid. Valve closure (the point at which the valve hits the stop corresponding to max armature stroke) is typically detected based on detecting an inflection point in the current profile. This method of closure detection is not reliable and is fundamentally flawed because the current profiles of valves can exhibit several other inflexion points due to bouncing (several closure events), non-linearity in valve inductance, back electromotive force (BEMF) characteristics, noise, etc. In addition, the open-loop approach requires a stiff power supply otherwise the valve closure might occur outside the narrow window used for closure detection. We describe how we applied model-based adaptive intelligence to reliably close the loop around valve closure using only the coil current feedback with the available CPU resources on the ECU without using special position sensors or other dedicated drive circuits. By appropriately controlling the drive voltage, we force the valve closure to correspond to a minimum (not an inflection) in the coil current feedback profile during the Pull-Hold event. This phenomenon is due to the loss of Back EMF the first time the valve hits its stop. This was tested on a wide range of valves of different sizes and designs. Practically this means that we can now reliably detect and control the time at which the valve hits the stop to within the time resolution of the current feedback profile (currently +/-15 microseconds). Alternatively, we can control the value of coil current at closure. Large variations in bus voltage in a non-stiff power supply, flow force variations, aging, etcetera, can be tolerated due to the close loop nature. Now the only hard piece of information required from the application is the value of the current required to hold the valve against the stop to complete the injection cycle. The rest of the information, namely the main electromechanical parameters of the valve and the drive voltage waveform are automatically determined by the adaptive intelligence that is run between shots for each valve. We will give actual measured final current profiles for the Woodward ERV (Electronic Rail Valve) and SOGAV (Solenoid-Operated Gas Admission Valve) together with a video sequence showing how the coil current profile is adapted from shot to shot as the adaptive algorithm improves its estimates of the basic valve parameters while it keeps tracking the closure point. We will also discuss some of the practical hurdles that we encountered in developing this into a product. Testing a range of valves also yielded "interesting" new findings that are also reported.
机译:螺线管致动喷射阀是由一个预定的电压或电流分布通常驱动开环。有阀电磁/机械参数的单元到单元的变化以及供电瞬变,流动力瞬变和操作条件而驱动电压或电流分布是固定的。因此,通过定义开环驱动器是次优的。广泛发动机校准是必要的所述衔铁的运动关联到在螺线管电流曲线。阀关闭(在该阀打对应于最大衔铁行程止点)的基础上在当前轮廓检测拐点通常检测。闭合检测的这种方法是不可靠的,基本上是错误的,因为阀的电流分布可表现出由于弹跳(几个闭合事件)几个其他拐点,非线性在阀电感,反电动势(BEMF)的特性,噪声,等。另外,在开环方法需要一个刚性的电源,否则阀闭合可能用于闭合检测的窄窗口之外发生。我们描述了如何使用只与ECU上的可用CPU资源的线圈电流反馈,而无需使用特殊的位置传感器或其他专用驱动电路采用基于模型的自适应智能可靠地封闭回路围绕阀门关闭。通过适当地控制驱动电压,我们的上拉保持事件期间迫使阀关闭,以对应于在线圈中的电流反馈简档的最小(未拐点)。这种现象是由于反电动势的损失首次阀引发其止损。将其在宽范围的不同尺寸和设计的阀测试。实际上,这意味着我们现在能够可靠地检测并控制该阀打停止电流反馈曲线(目前+/- 15微秒)的时间分辨率内的时间。可替代地,我们可以控制线圈电流的闭合的值。在总线电压大的变化在一非刚性电源,流动力的变化,老化,等等,可以由于闭环性质被容忍。现在唯一的硬片的从应用程序所需的信息是嫌弃停止阀门完成注射周期所需的电流值。的信息的其余部分,即该阀的主要机电参数和波形是由被拍摄为每个阀门之间运行自适应智能自动确定的驱动电压。我们将共同给予的伍德沃德ERV(电子轨道阀)和SOGAV(电磁控制的气体进入阀)实际测量的最终电流型材展示了如何线圈电流分布从镜头适合于拍摄的自适应算法提高了视频序列中的其估计基本阀参数的同时保持跟踪闭合点。我们还将讨论一些我们在开发成产品这中遇到的实际障碍。测试系列的阀门也产生了,它们也报道“有趣”的新发现。

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