摘 要
混合动力汽车（HEV）作为当前能源与环境问题的重要解决方案，其能量管理策略直接影响车辆的燃油经济性和排放性能。为优化HEV的能量分配，本研究基于规则的控制策略和模型预测控制方法，构建了适用于不同类型工况的仿真平台，并通过MATLAB/Simulink实现了对能量流的精确建模与分析。研究以提高燃油效率、降低排放为目标，提出了一种结合 Pontryagin 最优控制原理（PMP）与遗传算法（GA）的混合优化方法，该方法能够动态调整发动机与电机的工作状态，从而实现全局最优的能量分配。通过对城市循环工况（NEDC）和实际道路工况的对比测试，结果表明所提出的优化策略在燃油消耗方面较传统规则控制降低了约12%，同时显著减少了CO₂排放量。此外，本研究还探讨了电池老化对能量管理策略的影响，并提出了相应的补偿机制，进一步提升了系统的鲁棒性。研究的主要创新点在于将实时控制与全局优化相结合，为HEV能量管理策略的设计提供了新的思路，同时也为未来智能化控制技术的应用奠定了理论基础。
关键词：混合动力汽车；能量管理策略；Pontryagin最优控制原理；遗传算法；电池老化补偿
Abstract
Hybrid electric vehicles (HEVs) serve as a critical solution to current energy and environmental issues, with their energy management strategies directly impacting fuel economy and emission performance. To optimize the energy distribution in HEVs, this study constructs a simulation platform applicable to various driving conditions by integrating rule-based control strategies with model predictive control methods, and implements precise modeling and analysis of energy flow using MATLAB/Simulink. Aiming to enhance fuel efficiency and reduce emissions, a hybrid optimization approach combining Pontryagin's Minimum Principle (PMP) with Genetic Algorithm (GA) is proposed, which dynamically adjusts the operating states of the engine and motor to achieve globally optimal energy allocation. Through comparative testing under urban driving cycles (NEDC) and real-world road conditions, the results demonstrate that the proposed optimization strategy reduces fuel consumption by approximately 12% compared to traditional rule-based control, while significantly decreasing CO₂ emissions. Additionally, this research investigates the influence of battery aging on energy management strategies and proposes a corresponding compensation mechanism, further enhancing system robustness. The primary innovation of this study lies in the integration of real-time control with global optimization, offering new insights into the design of energy management strategies for HEVs and laying a theoretical foundation for the future application of intelligent control technologies.
Keywords: Hybrid Electric Vehicle；Energy Management Strategy；Pontryagin's Minimum Principle；Genetic Algorithm；Battery Aging Compensation
目 录
摘 要 I
Abstract II
一、绪论 1
（一）混合动力汽车能量管理策略的研究背景 1
（二）能量管理策略仿真与优化的意义分析 1
（三）国内外研究现状综述 2
二、混合动力汽车能量管理策略建模 2
（一）混合动力汽车系统架构概述 2
（二）能量管理策略的数学模型构建 3
（三）关键参数对能量管理的影响分析 3
三、能量管理策略仿真技术研究 4
（一）仿真平台的选择与搭建 4
（二）不同工况下的仿真测试方法 4
（三）仿真结果分析与验证 5
四、能量管理策略优化方法探讨 5
（一）常见优化算法在能量管理中的应用 5
（二）动态规划与遗传算法的对比研究 6
（三）优化策略的实际效果评估 7
结 论 7
致 谢 9
参考文献 10
