Advanced Intelligent Control of Next Generation Vehicles

下一代车辆的先进智能控制

• 批准号: 9460863
• 负责人: Richard Saeks
• 金额: $ 7.5万
• 依托单位: Accurate Automation Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1995
• 资助国家: 美国
• 起止时间: 1995-03-01 至 1996-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9460863&HistoricalAwards=false
• 关键词: Advanced; Intelligent; Control; Next; Generation

This SBIR Project will establish the feasibility of a neural network based advanced intelligent motor controller for fuel cell powered Next Generation Vehicles (NGV). The NGVs present control problems whose solution by conventional controller technology may present unacceptable technical, schedule, and cost risks. The neural network approach represents a revolutionary advancement to the field of vehicle control. The key objectives of this project are: to establish feasibility of a neural network based power control system for the NGV; to apply to 4 wheel, 4 motor vehicle configuration; to determine the optimal paradigm for NGV motor control; to determine optimal control by distributed vs. central control; to meet national goals of three-times fuel efficiency with marketable performance; and to plan and design for initial application to a bus in Phase II, then transition the controller to other vehicle classes in Phase III.

该SBIR项目将为燃料电池驱动的下一代汽车（NGV）建立基于神经网络的先进智能电机控制器的可行性。ngv存在控制问题，而采用常规控制器技术解决这些问题可能会带来不可接受的技术、进度和成本风险。神经网络方法代表了车辆控制领域的革命性进步。本课题的主要目标是：建立基于神经网络的NGV功率控制系统的可行性；适用于四轮、四轮机动车配置；确定NGV电机的最优控制模式；通过分布式控制和集中控制确定最优控制；以适销对路的性能达到三倍燃油效率的国家目标；并在第二阶段规划和设计初始应用于总线，然后在第三阶段将控制器过渡到其他车辆类别。