Optimization of Vaneless Volute and Mixed Flow Impeller for Pulsating Flow

Zheng Liu, C. Copeland, Stefan Tuechler
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Abstract

Vaneless turbocharger turbines are commonly used for automotive engines due to their low cost and better off-design performance. It consists of a vaneless volute and a radial or mixed flow rotor, where both components are important to the overall device performance. With the pulsating nature of the exhaust flows, most energy is contained at the peak of the pulse. Therefore, during one engine cycle, optimizing the turbine performance for the peak pulse region is more straightforward to improve the cycle-averaged shaft power generation. This study sought to optimize both the volute and rotor simultaneously for the peak point of the pressure pulse (2.4 bar). Thirteen design parameters in total are considered during the optimization process. Six volute design parameters were used to control the aspect ratio, intake area, exit area, and the circumferential distribution of the cross-sectional area. Seven rotor parameters were utilized to modify the cone angle, blade axial location, and the camber-line angle distribution. The optimization was conducted by a novel optimization algorithm based on Kriging surrogate model, and compared with the conventional genetic algorithm. Commercial turbulent viscous CFD solver ANSYS-CFX was used to predict the turbine performance. Full-stage turbine, including ten blade passages, is explicitly modeled for better accuracy. In order to ensure the matching between turbocharger and engine maintained the same as the original turbine, special attention was paid to constraint the swallowing capacity characteristic of the optimized turbine to be similar to the baseline turbine, with a maximum 2.5% difference at the design point. Compared with the baseline turbine, the turbine efficiency was improved by 3 percentage points with the using the genetic algorithm, and an improvement of 3.65 percentage points was achieved by using the Kriging surrogate model based optimization algorithm. Although the optimized turbine has a lower peak efficiency, the optimal velocity ratio of optimized design shifted from the baseline value of 0.71 to 0.61, implying a better performance will be achieved under high loading conditions. The improvement of the turbine performance is attributed to a better blade loading that is achieved in the 0.2–0.4 stream-wise location. The elementary effectiveness has been studied, and the camber-line distribution of the rotor is found to be the most influential factor on the turbine performance.
脉动流无叶蜗壳与混流叶轮的优化设计
无叶涡轮增压器涡轮通常用于汽车发动机,因为他们的低成本和更好的非设计性能。它由无叶蜗壳和径向或混合流转子组成,这两个部件对整体设备性能都很重要。由于排气流的脉动性质,大部分能量都包含在脉冲的峰值处。因此,在发动机一个循环周期内,优化峰值脉冲区域的涡轮性能更直接地提高循环平均轴发电量。本研究试图同时优化蜗壳和转子的压力脉冲峰值点(2.4 bar)。优化过程中共考虑了13个设计参数。采用6个蜗壳设计参数控制展弦比、进气面积、出口面积和横截面积的周向分布。利用7个转子参数来改变锥角、叶片轴向位置和弧线角分布。采用基于Kriging代理模型的优化算法进行优化,并与传统的遗传算法进行比较。利用商用湍流粘性CFD求解器ANSYS-CFX对涡轮性能进行了预测。全级涡轮,包括十个叶片通道,明确建模,以获得更好的精度。为了保证增压器与发动机的匹配与原涡轮保持一致,我们特别注意约束优化后涡轮的吞吞能力特性与基准涡轮相似,在设计点最大相差2.5%。与基线水轮机相比,采用遗传算法提高水轮机效率3个百分点,采用基于Kriging代理模型的优化算法提高水轮机效率3.65个百分点。虽然优化后的涡轮峰值效率较低,但优化设计的最佳速度比从基线值0.71转变为0.61,这意味着在高负荷条件下将获得更好的性能。涡轮性能的改善归功于在0.2-0.4流方向位置实现了更好的叶片负荷。对转子的基本有效性进行了研究,发现转子的弧线分布是影响涡轮性能的最主要因素。
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