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Comparison of the Extended Kalman Filter and the unscented Kalman filter for parameter estimation in combustion engines

机译:扩展卡尔曼滤波器与无味卡尔曼滤波器在内燃机参数估计中的比较

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In this article, two Kalman filtering techniques, the Un-scented Kalman Filter (UKF) and the Extended Kalman Filter (EKF) are applied for cylinder-wise torque estimation. In engine signal processing the problem of engine speed evaluation is one of the main problems of current research for engine control. In this work, two engine speed signals, recorded at the free end and at the flywheel, together with a multi-body model of the crankshaft are used to account for torsional deflections of the crankshaft. In order to estimate cylinder-wise torque, additionally one cylinder pressure signal is used to obtain a parametric torque model. The resulting parameter and state estimation problem allows the comparison of UKF and EKF. The performance of both algorithms was evaluated using measurements from a four cylinder combustion engine. Whilst practical issues still exist, this off-line study showed the feasibility of the approach.
机译:在本文中,将两种卡尔曼滤波技术(无味卡尔曼滤波器(UKF)和扩展卡尔曼滤波器(EKF))应用于汽缸转矩估计。在发动机信号处理中,发动机转速评估问题是当前发动机控制研究的主要问题之一。在这项工作中,在自由端和飞轮处记录的两个发动机转速信号与曲轴的多体模型一起用于说明曲轴的扭转变形。为了估计汽缸方向扭矩,另外使用一个汽缸压力信号来获得参数扭矩模型。由此产生的参数和状态估计问题允许UKF和EKF进行比较。使用四缸内燃机的测量结果评估了这两种算法的性能。尽管仍然存在实际问题,但这项离线研究表明了该方法的可行性。

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