ANALYSIS OF METHODS AND MEANS OF VEHICLE CONTROL SYSTEMS IN THE PROBLEM OF OPTIMAL CONTROL

Abstract

The article presents a comprehensive analysis of modern methods and tools for vehicle control systems in the context of optimal control tasks. Current problems in the development of intelligent autonomous transport systems that ensure optimal use of energy resources, minimization of transportation time, and maximization of payload are examined. Mathematical models of optimal control are analyzed in detail, including modeling of motion dynamics, electromagnetic processes in the drive, thermal processes, and component wear processes. Special attention is paid to electric drive diagnostic systems that use electrical methods, vibration diagnostics, thermal control, and artificial intelligence methods to detect malfunctions at early stages of development. Energy consumption optimization methods for electric vehicles are considered, including flux control strategies, energy recuperation during braking, and hybrid energy storage system management. Autonomous control systems based on comprehensive use of environmental perception sensors, trajectory planning algorithms, and motion control systems are analyzed. The role of intelligent transport systems in improving efficiency and safety of transport processes is highlighted. Development prospects related to the implementation of artificial intelligence technologies, quantum computing, and integration with renewable energy systems are outlined. The research demonstrates that modern vehicle control systems represent complex mechatronic complexes integrating various technologies including electronics, automation, information technologies, and artificial intelligence. The interdisciplinary nature of this field requires close cooperation between specialists of different specialties and coordinated efforts in solving common problems to ensure competitiveness of transport technologies.