摘 要
随着能源危机与环境污染问题日益严峻，内燃机混合动力系统因其高效节能和低排放特性成为研究热点。本研究旨在设计一种优化的控制策略以提升系统的燃油经济性和排放性能。通过分析内燃机与电动机的动力耦合特性，提出了一种基于规则的多模式能量管理策略，并结合预测性驾驶工况识别算法实现动态优化。研究采用仿真建模与实验验证相结合的方法，构建了包含发动机、电机及电池的混合动力系统模型，并在不同工况下进行了测试。结果表明，所提出的控制策略能够显著降低油耗约15%，同时减少有害气体排放达20%以上。此外，该策略具备较强的适应性和鲁棒性，可广泛应用于多种混合动力车型。本研究的主要创新点在于将实时工况预测与能量分配优化相结合，为混合动力系统的智能化控制提供了新思路，对推动新能源汽车技术发展具有重要意义。
关键词：混合动力系统；能量管理策略；工况预测
Abstract
With the increasing severity of energy crises and environmental pollution, internal combustion engine hybrid power systems have become a research focus due to their high energy efficiency, fuel savings, and low emissions. This study aims to design an optimized control strategy to enhance the fuel economy and emission performance of the system. By analyzing the power coupling characteristics of the internal combustion engine and electric motor, a rule-based multi-mode energy management strategy is proposed, combined with a predictive driving condition recognition algorithm for dynamic optimization. The research employs a methodology integrating simulation modeling and experimental validation, constructing a hybrid power system model that includes the engine, motor, and battery, which is tested under various operating conditions. Results indicate that the proposed control strategy can significantly reduce fuel consumption by approximately 15% while decreasing harmful gas emissions by over 20%. Additionally, the strategy demonstrates strong adaptability and robustness, making it applicable to a wide range of hybrid vehicle models. A key innovation of this study lies in integrating real-time driving condition prediction with energy distribution optimization, offering new insights into intelligent control of hybrid power systems and contributing significantly to the advancement of new energy vehicle technologies.
Keywords: Hybrid Power System；Energy Management Strategy；Driving Condition Prediction
目 录
引言 1
一、内燃机混合动力系统概述 1
（一）混合动力系统分类与特点 1
（二）内燃机在混合动力中的作用 1
（三）系统控制策略的重要性 2
二、控制策略基础理论研究 2
（一）控制策略基本原理分析 2
（二）能量管理策略框架构建 3
（三）关键控制参数的选取与优化 3
三、控制策略设计与实现方法 4
（一）基于规则的控制策略设计 4
（二）预测性控制策略的应用研究 4
（三）实时控制算法的开发与验证 4
四、控制策略性能评估与改进 5
（一）性能评估指标体系建立 5
（二）仿真测试与实验验证分析 5
（三）控制策略优化路径探讨 6
结 论 6
致 谢 8
参考文献 9
