ISG混合动力城市客车动力系统集成与优化控制研究
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摘要
混合动力汽车(HEV)是一种低能耗、低排放、技术成熟、成本适中、兼具纯电动汽车和传统内燃机汽车优点的新能源汽车。同时,混合动力汽车已被证实是短期内可以取代传统内燃机车的清洁汽车。混合动力轿车的应用已经得到迅速的推广,但是混合动力城市客车和商用车的开发和研究起步较晚,还不成熟。由于ISG混合动力系统以其对原车改动小、适应性强、可靠性好、易于产业化推广等特点,近年来,不少企业与高校合作进行了ISG混合动力汽车的开发并取得实质性进展。
混合动力汽车动力系统的集成与优化是混合动力汽车开发的关键技术之一,是提高混合动力汽车综合性能的前提条件。本课题结合厂校重大合作项目“混合动力城市公交车的开发”,对ISG混合动力客车的动力系统进行了优化匹配和设计。根据ISG混合动力客车的工作特点和功能要求,提出了一种基于混合度的高效混合动力系统匹配优化方法,该方法可以最大限度地缩短开发时间,降低开发成本。主要从以下三个方面展开:根据ISG混合动力客车的工作特点和性能要求,初步确定了混合动力客车发动机、ISG电机和电池的选型;采用模块化的思想,在Matlab/Simulink环境下,建立了混合动力客车前向仿真平台和整车控制策略模型,并对该模型进行了试验验证;利用该仿真平台,对混合动力汽车的混合度进行了深入的研究和优化,确定最佳混合度,实现城市混合动力客车动力总成参数的优化匹配。
混合动力总成系统参数匹配与多能源管理策略的优劣对混合动力汽车的性能起到关键的作用。就目前研究状态来看,对既定的混合动力总成参数匹配进行评估,对混合动力系统的能量分配控制策略做出评价是一个迫切需要解决的问题。评估混合动力性能的关键指标就是燃油经济性及排放性能。基于工程经验的控制策略,对燃油经济性,排放性及两者的最佳平衡往往难以给出确切的答案。本文构建了带权值的油耗和排放的目标函数,利用动态规划优化算法DP(Dynamic Programming),求解该目标函数的最小值,对混合动力总成参数的优化结果进行验证,对燃油经济性和排放改善的潜力进行了分析,从而达到对能量分配策略的分析与评估的目的。由于DP优化算法的控制变量和状态变量维数多,迭代次数多,计算量巨大,从而计算速度慢,费时费力。本文发现并利用控制变量和状态变量的之间的确定关系,对常规的动态算法进行改进,大大提高了运算速度与精度。由于动态规划是一种基于固定工况的全局优化方法,而实际工况具有随机性和不可预测性的特点,因此动态规划算法并不具备实时控制的特点,不能实现在线实时优化控制。本文对动态规划的离线优化仿真结果进行了分析,从中提取规律,制定了一个基于动态规划结果的实时控制策略RTCS-DP(Realtime Control Strategy based on Dynamic Programming),取得了较好的效果。
在本文的最后,对ISG混合动力总成的优化匹配结果和RTCS-DP控制策略进行了台架试验和实车试验。关键零部件的台架试验为混合动力系统建模和控制策略的设计提供了必要的数据。道路试验结果表明,在保证SOC平衡的条件下,混合动力系统实现预期的工作模式和模式间的平滑切换。相对传统汽车,本项目提出的ISG混合动力总成及RTCS-DP在中国典型城市工况下燃油经济性提高近22.7%,实车试验结果和仿真结果非常接近。测试结果表明,本文所提出的混合动力系统进行性能匹配与优化方法是可行的,不但加快了开发进度,而且还节省了大量的开发费用,对混合动力汽车的研究和开发具有一定的应用价值和学术价值。
Hybrid Electric Vehicle (HEV) is a new energy vehicle with high fuel economy, low emissions and low cost compared with other vehicles. HEVs include the advantages of pure electric vehicle and conventional engine-only powered vehicles and are assumed to be the most promising alternative to a conventional vehicle in the near future. The hybrid electric passage cars have become available in the market and widely used in all over the world, while the technology research of hybrid electric bus and commercial vehicle is not well developed. ISG (Integrated Starter Generator) HEV is newly developed powertrain with high reliability, low cost and easy to accept for the market. Many company, university and institutes are engaged in this research and development with great achievement.
The powertrain integration and optimization is one of the key technologies for hybrid electric vehicle to improve the fuel economy and emissions. Based on the university and factory cooperative project“The Development of Hybrid Electric Bus”, a high efficient system integration and optimization method is proposed according to function requirement and ISG hybrid electric bus characteristics. This method can shorten both the development time and cost. It can be summarized as followings. According to the characters and performance requirements, the type of engine, ISG and battery are selected; Hybrid electric bus simulation platform and control strategy are modeled and validated in Matlab/Simulink environment; the hybrid factor of the hybrid electric bus is optimized to determine the power of engine and motor.
According to ISG hybrid electric bus characteristics and performance requirement, the type and candidate size of engine, ISG motor and battery are selected. A simulation platform of hybrid electric bus is developed and validated in Matlab/Simulink/Stateflow environment with a Hybrid Control Unit (HCU) model. The control strategy and powertrain parameter match are researched through the simulation over the typical urban driving cycles to select the most suitable power of ISG powertrain.
For a particular hybrid electric vehicle, the hybrid powertrain and control strategy have important effect for the fuel economy and emission performance. Whether it can reduce fuel consumption and emission or not and how much is them are always problem. For a specific engineering experience based control strategy, it is difficult to determine whether it is the most optimization control strategy or not and whether is it fully explored the potential of hybrid electric vehicle or not. In order to investigate the potential of diesel engine hybrid electric vehicles in fuel economy improvement and emissions reduction, a Dynamic Programming (DP) based supervisory controller is developed to allocate the power requirement between ICE and batteries with the objective of minimizing a weighted cost function over given drive cycles. The DP is time and energy consumption algorithm with massive of control and state variables. The relationship between the control variable and state variable is found and a new DP algorithm is proposed to shorten the calculation time and improve the accuracy in this dissertation. The DP is not a real-time optimization algorithm which is based on a given driving cycle to explore the global optimization while the real road driving is random and unpredictable. The offline DP optimization results can be analyzed and some implemental rules or laws can be extracted from the results and applied to real-time control strategies. A real-time control strategy is proposed based on the DP optimization results. That is RTCS-DP ( Real-time Control Strategy based on Dynamic Programming) control strategy which is near global optimization control strategy.
The bench test and field test results of the ISG hybrid electric bus are presents at the last part of this dissertation. The bench tests results of the components are validated the components model and control strategy. The tests are undertaken on dynamometer and real road test. Compared with the conventional bus, the ISG bus fuel economy has improved 21.7% under the China Urban Driving Cycle with the SOC sustainable. The test results demonstrate that the method of system integration and optimization proposed in this dissertation is useful in speed up the hybrid electric vehicle development and improving the domestic research and development of the HEV.
混合动力汽车动力系统的集成与优化是混合动力汽车开发的关键技术之一,是提高混合动力汽车综合性能的前提条件。本课题结合厂校重大合作项目“混合动力城市公交车的开发”,对ISG混合动力客车的动力系统进行了优化匹配和设计。根据ISG混合动力客车的工作特点和功能要求,提出了一种基于混合度的高效混合动力系统匹配优化方法,该方法可以最大限度地缩短开发时间,降低开发成本。主要从以下三个方面展开:根据ISG混合动力客车的工作特点和性能要求,初步确定了混合动力客车发动机、ISG电机和电池的选型;采用模块化的思想,在Matlab/Simulink环境下,建立了混合动力客车前向仿真平台和整车控制策略模型,并对该模型进行了试验验证;利用该仿真平台,对混合动力汽车的混合度进行了深入的研究和优化,确定最佳混合度,实现城市混合动力客车动力总成参数的优化匹配。
混合动力总成系统参数匹配与多能源管理策略的优劣对混合动力汽车的性能起到关键的作用。就目前研究状态来看,对既定的混合动力总成参数匹配进行评估,对混合动力系统的能量分配控制策略做出评价是一个迫切需要解决的问题。评估混合动力性能的关键指标就是燃油经济性及排放性能。基于工程经验的控制策略,对燃油经济性,排放性及两者的最佳平衡往往难以给出确切的答案。本文构建了带权值的油耗和排放的目标函数,利用动态规划优化算法DP(Dynamic Programming),求解该目标函数的最小值,对混合动力总成参数的优化结果进行验证,对燃油经济性和排放改善的潜力进行了分析,从而达到对能量分配策略的分析与评估的目的。由于DP优化算法的控制变量和状态变量维数多,迭代次数多,计算量巨大,从而计算速度慢,费时费力。本文发现并利用控制变量和状态变量的之间的确定关系,对常规的动态算法进行改进,大大提高了运算速度与精度。由于动态规划是一种基于固定工况的全局优化方法,而实际工况具有随机性和不可预测性的特点,因此动态规划算法并不具备实时控制的特点,不能实现在线实时优化控制。本文对动态规划的离线优化仿真结果进行了分析,从中提取规律,制定了一个基于动态规划结果的实时控制策略RTCS-DP(Realtime Control Strategy based on Dynamic Programming),取得了较好的效果。
在本文的最后,对ISG混合动力总成的优化匹配结果和RTCS-DP控制策略进行了台架试验和实车试验。关键零部件的台架试验为混合动力系统建模和控制策略的设计提供了必要的数据。道路试验结果表明,在保证SOC平衡的条件下,混合动力系统实现预期的工作模式和模式间的平滑切换。相对传统汽车,本项目提出的ISG混合动力总成及RTCS-DP在中国典型城市工况下燃油经济性提高近22.7%,实车试验结果和仿真结果非常接近。测试结果表明,本文所提出的混合动力系统进行性能匹配与优化方法是可行的,不但加快了开发进度,而且还节省了大量的开发费用,对混合动力汽车的研究和开发具有一定的应用价值和学术价值。
Hybrid Electric Vehicle (HEV) is a new energy vehicle with high fuel economy, low emissions and low cost compared with other vehicles. HEVs include the advantages of pure electric vehicle and conventional engine-only powered vehicles and are assumed to be the most promising alternative to a conventional vehicle in the near future. The hybrid electric passage cars have become available in the market and widely used in all over the world, while the technology research of hybrid electric bus and commercial vehicle is not well developed. ISG (Integrated Starter Generator) HEV is newly developed powertrain with high reliability, low cost and easy to accept for the market. Many company, university and institutes are engaged in this research and development with great achievement.
The powertrain integration and optimization is one of the key technologies for hybrid electric vehicle to improve the fuel economy and emissions. Based on the university and factory cooperative project“The Development of Hybrid Electric Bus”, a high efficient system integration and optimization method is proposed according to function requirement and ISG hybrid electric bus characteristics. This method can shorten both the development time and cost. It can be summarized as followings. According to the characters and performance requirements, the type of engine, ISG and battery are selected; Hybrid electric bus simulation platform and control strategy are modeled and validated in Matlab/Simulink environment; the hybrid factor of the hybrid electric bus is optimized to determine the power of engine and motor.
According to ISG hybrid electric bus characteristics and performance requirement, the type and candidate size of engine, ISG motor and battery are selected. A simulation platform of hybrid electric bus is developed and validated in Matlab/Simulink/Stateflow environment with a Hybrid Control Unit (HCU) model. The control strategy and powertrain parameter match are researched through the simulation over the typical urban driving cycles to select the most suitable power of ISG powertrain.
For a particular hybrid electric vehicle, the hybrid powertrain and control strategy have important effect for the fuel economy and emission performance. Whether it can reduce fuel consumption and emission or not and how much is them are always problem. For a specific engineering experience based control strategy, it is difficult to determine whether it is the most optimization control strategy or not and whether is it fully explored the potential of hybrid electric vehicle or not. In order to investigate the potential of diesel engine hybrid electric vehicles in fuel economy improvement and emissions reduction, a Dynamic Programming (DP) based supervisory controller is developed to allocate the power requirement between ICE and batteries with the objective of minimizing a weighted cost function over given drive cycles. The DP is time and energy consumption algorithm with massive of control and state variables. The relationship between the control variable and state variable is found and a new DP algorithm is proposed to shorten the calculation time and improve the accuracy in this dissertation. The DP is not a real-time optimization algorithm which is based on a given driving cycle to explore the global optimization while the real road driving is random and unpredictable. The offline DP optimization results can be analyzed and some implemental rules or laws can be extracted from the results and applied to real-time control strategies. A real-time control strategy is proposed based on the DP optimization results. That is RTCS-DP ( Real-time Control Strategy based on Dynamic Programming) control strategy which is near global optimization control strategy.
The bench test and field test results of the ISG hybrid electric bus are presents at the last part of this dissertation. The bench tests results of the components are validated the components model and control strategy. The tests are undertaken on dynamometer and real road test. Compared with the conventional bus, the ISG bus fuel economy has improved 21.7% under the China Urban Driving Cycle with the SOC sustainable. The test results demonstrate that the method of system integration and optimization proposed in this dissertation is useful in speed up the hybrid electric vehicle development and improving the domestic research and development of the HEV.
引文
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