摘要
混合动力汽车作为传统燃油汽车与纯电动汽车之间的过渡产品，在节能减排方面具有重要意义，其能量管理策略直接关系到车辆的燃油经济性和排放性能。本研究旨在优化混合动力汽车的能量管理策略，通过建立包含发动机、电机、电池等部件在内的整车模型，采用动态规划算法和基于规则的控制策略相结合的方法进行研究。首先利用动态规划算法求解全局最优解，得到不同工况下的理想工作模式切换规律及功率分配方案，然后以此为依据设计基于规则的控制策略，以实现近似全局最优解且便于实际应用。结果表明，所提出的能量管理策略能够有效提高车辆的燃油经济性，在城市循环工况下相比传统策略节油率提升了约15%，在郊区循环工况下节油率提升了约10%。同时，该策略还兼顾了动力性和排放性能，使车辆的动力响应更加迅速和平顺，有害气体排放量也有所降低。本研究创新性地将动态规划算法与基于规则的控制策略结合应用于混合动力汽车能量管理策略的研究，不仅提高了车辆综合性能，还为后续相关研究提供了新的思路和方法。
关键词：混合动力汽车；能量管理策略；动态规划算法
Abstract
Hybrid electric vehicles (HEVs), serving as a transitional product between conventional internal combustion engine vehicles and pure electric vehicles, play a significant role in energy conservation and emission reduction. The energy management strategy of HEVs directly affects the vehicle's fuel economy and emission performance. This study aims to optimize the energy management strategy for HEVs by developing a comprehensive vehicle model that incorporates components such as the engine, motor, and battery. A combined approach using dynamic programming algorithms and rule-based control strategies is employed. Initially, the dynamic programming algorithm is utilized to solve for the global optimal solution, determining the ideal switching patterns of operating modes and power distribution schemes under various driving conditions. Subsequently, based on these findings, a rule-based control strategy is designed to achieve an approximate global optimum while ensuring practical applicability. The results indicate that the proposed energy management strategy effectively enhances the vehicle's fuel economy, achieving approximately a 15% improvement in fuel efficiency in urban driving cycles and about a 10% improvement in suburban driving cycles compared to traditional strategies. Moreover, this strategy also improves the vehicle's dynamic performance and emission characteristics, resulting in more rapid and smoother power responses and reduced emissions of harmful gases. Innovatively, this research integrates dynamic programming algorithms with rule-based control strategies in the study of HEV energy management, not only improving the overall vehicle performance but also providing new insights and methodologies for future related studies.
Keywords：Hybrid Electric Vehicle; Energy Management Strategy; Dynamic Programming Algorithm
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) 研究的意义与价值 1
(三) 国内外研究现状综述 1
(四) 本文研究方法与技术路线 2
二、混合动力汽车能量管理策略的理论基础 2
(一) 混合动力汽车工作原理 2
(二) 能量流分析与建模 3
(三) 控制策略分类与特点 3
(四) 理论基础对优化策略的指导意义 4
三、混合动力汽车能量管理策略的优化方法 5
(一) 基于规则的控制策略优化 5
(二) 基于模型预测的控制策略 5
(三) 机器学习在能量管理中的应用 6
(四) 多目标优化算法的应用 6
四、混合动力汽车能量管理策略的实验验证 7
(一) 实验平台搭建与测试方案 7
(二) 不同工况下的性能测试 8
(三) 优化前后对比分析 8
(四) 实验结果与讨论 9
结 论 11
参考文献 12
混合动力汽车作为传统燃油汽车与纯电动汽车之间的过渡产品，在节能减排方面具有重要意义，其能量管理策略直接关系到车辆的燃油经济性和排放性能。本研究旨在优化混合动力汽车的能量管理策略，通过建立包含发动机、电机、电池等部件在内的整车模型，采用动态规划算法和基于规则的控制策略相结合的方法进行研究。首先利用动态规划算法求解全局最优解，得到不同工况下的理想工作模式切换规律及功率分配方案，然后以此为依据设计基于规则的控制策略，以实现近似全局最优解且便于实际应用。结果表明，所提出的能量管理策略能够有效提高车辆的燃油经济性，在城市循环工况下相比传统策略节油率提升了约15%，在郊区循环工况下节油率提升了约10%。同时，该策略还兼顾了动力性和排放性能，使车辆的动力响应更加迅速和平顺，有害气体排放量也有所降低。本研究创新性地将动态规划算法与基于规则的控制策略结合应用于混合动力汽车能量管理策略的研究，不仅提高了车辆综合性能，还为后续相关研究提供了新的思路和方法。
关键词：混合动力汽车；能量管理策略；动态规划算法
Abstract
Hybrid electric vehicles (HEVs), serving as a transitional product between conventional internal combustion engine vehicles and pure electric vehicles, play a significant role in energy conservation and emission reduction. The energy management strategy of HEVs directly affects the vehicle's fuel economy and emission performance. This study aims to optimize the energy management strategy for HEVs by developing a comprehensive vehicle model that incorporates components such as the engine, motor, and battery. A combined approach using dynamic programming algorithms and rule-based control strategies is employed. Initially, the dynamic programming algorithm is utilized to solve for the global optimal solution, determining the ideal switching patterns of operating modes and power distribution schemes under various driving conditions. Subsequently, based on these findings, a rule-based control strategy is designed to achieve an approximate global optimum while ensuring practical applicability. The results indicate that the proposed energy management strategy effectively enhances the vehicle's fuel economy, achieving approximately a 15% improvement in fuel efficiency in urban driving cycles and about a 10% improvement in suburban driving cycles compared to traditional strategies. Moreover, this strategy also improves the vehicle's dynamic performance and emission characteristics, resulting in more rapid and smoother power responses and reduced emissions of harmful gases. Innovatively, this research integrates dynamic programming algorithms with rule-based control strategies in the study of HEV energy management, not only improving the overall vehicle performance but also providing new insights and methodologies for future related studies.
Keywords：Hybrid Electric Vehicle; Energy Management Strategy; Dynamic Programming Algorithm
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) 研究的意义与价值 1
(三) 国内外研究现状综述 1
(四) 本文研究方法与技术路线 2
二、混合动力汽车能量管理策略的理论基础 2
(一) 混合动力汽车工作原理 2
(二) 能量流分析与建模 3
(三) 控制策略分类与特点 3
(四) 理论基础对优化策略的指导意义 4
三、混合动力汽车能量管理策略的优化方法 5
(一) 基于规则的控制策略优化 5
(二) 基于模型预测的控制策略 5
(三) 机器学习在能量管理中的应用 6
(四) 多目标优化算法的应用 6
四、混合动力汽车能量管理策略的实验验证 7
(一) 实验平台搭建与测试方案 7
(二) 不同工况下的性能测试 8
(三) 优化前后对比分析 8
(四) 实验结果与讨论 9
结 论 11
参考文献 12
