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Investigation of advanced engine cooling systems - Optimization and nonlinear control.

机译:高级发动机冷却系统的研究-优化和非线性控制。

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摘要

Advanced automotive engine cooling systems can positively impact the performance, fuel economy, and reliability of internal combustion engines. A smart engine cooling system typically features multiple real time computer controlled actuators: a three way linear smart valve, a variable speed coolant pump, and electric radiator fan(s). In this dissertation, several innovative comprehensive nonlinear control and optimization operation strategies for the next generation smart cooling application will be analyzed.;First, the optimal control has been investigated to minimize the electric energy usage of radiator fan matrix. A detailed mathematical model of the radiator fan(s) matrix operation and the forced convection heat transfer process was developed to establish a mixed integer nonlinear programming problem. An interior points approach was introduced to solve the energy consumption minimization problem. A series of laboratory tests have been conducted with different fan configurations and rotational shaft speed combinations, with the objective to cool a thermal loaded engine. Both the mathematical approach and the laboratory test results demonstrated the effectiveness of similar control strategies. Based on the tests data and mathematical analysis, an optimization control strategy reduced the fan matrix power consumption by up to 67%.;Second, a series of experimental laboratory tests were implemented to investigate the contributions of each electro-mechanical device in automotive thermal management system. The test results established a basis for several key operating conclusions. The smart valve and variable speed pump impacted the engine temperature by adjusting the heat transfer rate between the engine and the radiator through coolant redirection and/or coolant flow rate. On the other hand, the radiator fan(s) operation affects the engine's temperature by modifying the heat rejection rate of the radiator which can influence the entire cooling system. In addition, the smart valve's operation changes the engine's temperature magnitude the greatest amount followed by the radiator fan(s) and the coolant pump. Furthermore, from a power consumption aspect, the radiator fan(s) consumes the most engine power in comparison to the two other actuators.;Third, a Lyapunov based nonlinear control strategy for the radiator fan matrix was studied to accommodate transient engine temperature tracking at heavy heat load. A reduced order mathematical model established a basis for the closed-loop real time feedback system. Representative numerical and experimental tests demonstrated that the advanced control strategy can regulate the engine temperature tracking error within 0.12°C and compensate the unknown heat load. The nonlinear controller provided superior performance in terms of power consumption and temperature tracking as evident by the reduced magnitude when compared to a classical proportional integral with lookup table based controller and a bang bang controller.;Fourth, a nonlinear adaptive multiple-input and multiple-output (NAMIMO) controller to operate the smart valve and radiator fans has been presented. This controller regulates the engine temperature while compensating for unknown wide range heat loads and ram air effects. A nonlinear adaptive backstepping (NAB) control strategy and a state flow (SF) control law were introduced for comparisons. The test results indicated that the NAMIMO successfully regulated the engine temperature to a desired value (tracking error, |e|<0.5° C, at steady state) subject to various working conditions. In contrast, the NAB control law consumes the least radiator fan power but demonstrated a larger average temperature tracking error (40% greater than the NAMIMO controller), a longer response time (34% greater than the NAMIMO controller), and defected when the heat load was low. Lastly, the SF controller, characterized by greater oscillation and electrical power consumption (18.9% greater than the NAMIMO controller), was easy to realize and maintained the engine temperature to within |e|<5°C.;An important aspect of engineering research is the knowledge gained from learning materials to fully understand the thermal management. As part of the dissertation, advanced three-dimensional (3D) visualization and virtual reality (VR) technology based engineering education methods has been studied. A series of computer aided design (CAD) models with storyboards have been created to provide a step to step guide for developing the learning modules. The topics include automotive, aerospace, and manufacturing. The center for aviation and automotive technological education using virtual e-schools (CA2VES) at Clemson University has developed a comprehensive e-learning system integrated with eBooks, mini video lectures, 3D virtual reality technologies, and online assessments as supplementary materials to engineering education.
机译:先进的汽车发动机冷却系统可以对内燃机的性能,燃油经济性和可靠性产生积极影响。智能引擎冷却系统通常具有多个实时计算机控制的执行器:三通线性智能阀,变速冷却液泵和电散热器风扇。本文针对下一代智能冷却应用,分析了几种创新的综合非线性控制和优化运行策略。首先,研究了最优控制以最小化散热器风扇矩阵的电能消耗。建立了散热器风扇矩阵运行和强制对流传热过程的详细数学模型,以建立混合整数非线性规划问题。引入了内部积分方法来解决能耗最小化的问题。为了冷却热负荷发动机,已经针对不同的风扇配置和旋转轴转速组合进行了一系列实验室测试。数学方法和实验室测试结果都证明了类似控制策略的有效性。根据测试数据和数学分析,优化控制策略可将风扇矩阵功耗降低多达67%。其次,进行了一系列实验实验室测试,以研究每种机电设备在汽车热管理中的作用。系统。测试结果为几个关键操作结论奠定了基础。智能阀和变速泵通过冷却剂重定向和/或冷却剂流量调节发动机和散热器之间的传热速率,从而影响了发动机温度。另一方面,散热器风扇的运行通过修改散热器的散热率来影响发动机的温度,从而影响整个冷却系统。此外,智能阀的运行会最大程度地改变发动机的温度幅度,随后是散热器风扇和冷却液泵。此外,从功耗方面来看,与其他两个执行器相比,散热器风扇消耗的发动机功率最多。第三,研究了基于Lyapunov的散热器风扇矩阵非线性控制策略,以适应瞬态发动机温度跟踪。高热负荷。降阶数学模型为闭环实时反馈系统奠定了基础。代表性的数值和实验测试表明,先进的控制策略可以在0.12°C的范围内调节发动机温度跟踪误差并补偿未知的热负荷。非线性控制器在功耗和温度跟踪方面提供了卓越的性能,与传统的比例积分式基于查找表的控制器和爆炸控制器相比,幅度减小了。第四,非线性自适应多输入多输入已经介绍了用于操作智能阀和散热器风扇的输出(NAMIMO)控制器。该控制器调节发动机温度,同时补偿未知的大范围热负荷和冲压空气影响。为了进行比较,引入了非线性自适应反推(NAB)控制策略和状态流(SF)控制律。测试结果表明,在各种工况下,NAMIMO成功地将发动机温度调节至所需值(稳态时,跟踪误差| e | <0.5°C)。相比之下,NAB控制法则消耗的散热器风扇功率最少,但表现出更大的平均温度跟踪误差(比NAMIMO控制器大40%),更长的响应时间(比NAMIMO控制器大34%),并且在散热时出现缺陷负载低。最后,SF控制器具有更大的振荡和更多的电能消耗(比NAMIMO控制器大18.9%),易于实现并将发动机温度保持在| e | <5°C以内。;工程研究的一个重要方面是从学习材料中获得的知识,可以充分理解热管理。作为研究的一部分,研究了基于先进的三维(3D)可视化和虚拟现实(VR)技术的工程教学方法。已经创建了带有情节提要的一系列计算机辅助设计(CAD)模型,以提供开发学习模块的逐步指导。主题包括汽车,航空航天和制造业。克莱姆森大学使用虚拟电子学校(CA2VES)的航空和汽车技术教育中心已经开发了一个综合的电子学习系统,该系统集成了电子书,微型视频讲座,3D虚拟现实技术以及在线评估,作为工程教育的补充材料。

著录项

  • 作者

    Wang, Tianwei Thomas.;

  • 作者单位

    Clemson University.;

  • 授予单位 Clemson University.;
  • 学科 Mechanical engineering.;Automotive engineering.
  • 学位 Ph.D.
  • 年度 2016
  • 页码 181 p.
  • 总页数 181
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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