Advanced Intelligent Control of Next Generation Vehicles

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带来了控制问题，传统控制器技术的解决方案可能会带来不可接受的技术、进度和成本风险。神经网络方法代表着车辆控制领域的革命性进步。该项目的主要目标是：建立基于神经网络的NGV动力控制系统的可行性；应用于四轮四机动车辆配置；确定NGV电机控制的最佳范例；确定分布式控制与集中式控制的最佳控制；以市场性能满足国家三倍燃油效率的目标；并规划和设计在第二阶段将控制器初步应用于公交车，然后在第三阶段将控制器过渡到其他车辆类别。

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.