首页> 外文会议>ASME Internal Combustion Engine Division technical conference >ROBUST FEED-FORWARD CONTROLS FOR BETTER TRACKING: A PRACTICAL APPROACH TO OPTIMAL AIR-FUEL CONTROLS LOW EMISSIONS
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ROBUST FEED-FORWARD CONTROLS FOR BETTER TRACKING: A PRACTICAL APPROACH TO OPTIMAL AIR-FUEL CONTROLS LOW EMISSIONS

机译:强大的前馈控制,以更好地跟踪:最佳空气燃料控制和低排放的实用方法

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When designing control systems, it is important to keep in mind the end-users. In general, the complexity and difficulty of implementing and tuning a control strategy determine if such a strategy should be adopted, despite its performance. The automotive industry is no exception to that; powertrain control system engineers are constantly tasked to design controllers that are simple to follow, fairly robust, and require moderate resources for implementation and validation. Obviously, stability is critical for any control strategy; an oscillating controller not only could result in fluctuation in engine torque which could lead to customer dissatisfaction, but also could have a negative impact on vehicle tailpipe emissions. Bottom line is the controller must provide good stability as well as superb reference tracking. Proportional-Integral-Derivative (PID) controllers are attractive solutions for powertrain calibrators. They are widely used in the automotive industry as they are easy to implement and tune, especially when the Derivative term is dropped to reduce the sensitivity of the system and improve its robustness. Consequently, with only two gains to adjust, tuning a PI controller is a relatively simple task, but quite often calibrators struggle trying to meet both stability requirements and tracking performance. Adding a Smith Predictor (SP) to the PI controller, is one way to achieve the tracking performance desired. This is indeed a well known approach that allows for much higher gains to be used in order to improve the tracking ability while maintaining stability in the presence of plant models changing dynamics and system delays. However, with this combination (PI-SP), the robustness of the overall control strategy suffers as errors in the plant models tend to reduce the stability of the over all system and could potentially lead to an unstable or undesirable performance. In this paper, we will present a practical approach to improve the performance and robustness of the PI controller. This is achieved by adding unity-gain feed-forward (FF) of the air fuel set point for improved tracking plus a set-point filter in the input to the PI controller (FF-PI) to prevent overshoots. We will also show that this control structure provides excellent and robust reference tracking without destabilizing the system in the presence of errors in the plant model. In addition, we will include results obtained with the FF-PI controller when applied to two applications: Air-fuel ratio (A/F) control for gasoline lean burn vehicles (5.4L F150 and 4.0L Ford of Australia Falcon), and Exhaust Gas Recirculation (EGR) control on a 2.0L Gasoline, Turbocharged, Direct Injection Engine.
机译:在设计控制系统时,请记住最终用户非常重要。通常,尽管其表现,但实施控制策略的复杂性和难度决定了是否采用了这样的策略。汽车行业对此并不例外;动力总成控制系统工程师不断任务,设计易于遵循,相当强劲的控制器,并需要适度的资源来实现和验证。显然,稳定性对于任何控制策略至关重要;振荡控制器不仅可能导致发动机扭矩波动,这可能导致客户不满,但也可能对车辆尾管排放产生负面影响。底线是控制器必须提供良好的稳定性以及优秀的参考跟踪。比例积分衍生物(PID)控制器是动力总成校准器的吸引力解决方案。它们广泛用于汽车行业,因为它们易于实施和调整,特别是当衍生术语被丢弃以降低系统的灵敏度并提高其鲁棒性。因此,只需调整两个增益,调整PI控制器是一个相对简单的任务,但通常校准器试图满足稳定性要求和跟踪性能。将史密斯预测器(SP)添加到PI控制器,是实现所需跟踪性能的一种方法。这实际上是一种众所周知的方法,允许使用更高的收益来改善跟踪能力,同时保持植物模型的存在变化动态和系统延迟的稳定性。然而,通过这种组合(PI-SP),整体控制策略的稳健性遭受植物模型中的误差倾向于降低所有系统的稳定性,并且可能导致不稳定或不希望的性能。在本文中,我们将提出一种改善PI控制器的性能和鲁棒性的实用方法。这是通过在输入到PI控制器(FF-PI)的输入中添加通气燃料设定点的单位增益前馈(FF)来实现,以改进跟踪加上PI控制器(FF-PI)的设定点滤波器以防止过冲。我们还将表明,该控制结构提供出色和强大的参考跟踪,而不会在植物模型中存在错误的情况下使系统的存在不稳定。此外,我们将包括在应用于两个应用时用FF-PI控制器获得的结果:汽油瘦燃烧车辆的空燃比(A / F)控制(5.4L F150和4.0L澳大利亚猎鹰福特)和排气燃气再循环(EGR)对2.0L汽油,涡轮增压,直喷发动机的控制。

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