串联型液压混合动力汽车的能量管理策略研究
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摘要
近年来，随着经济的发展，公路运输规模和运输汽车数量都在不断增加，运输汽车的燃油消耗量也相应地大幅增长，因此提高运输汽车燃油经济性的需求越来越强烈，这极大地促进了与运输汽车相关的新能源汽车的研究和发展。在这些研究中，采用液压混合动力技术来提高运输汽车的燃油经济性非常具有吸引力。其一，运输汽车一般质量较大，需要的驱动功率也较高；其二，液压系统的一些优秀性能，比如液压泵/马达具有很高的功率密度和效率，液压储能器能够在其整个工作范围内进行快充和快放等，使其非常适合应用于运输汽车的混合动力系统中。因此，液压混合动力技术被视为能有效降低运输汽车耗油量的最可行的技术。然而，液压储能器的能量密度低也给这项技术的应用带来一些挑战。正是液压混合动力技术所面临的这些机遇和挑战使其成为目前混合动力汽车研究领域的热点之一。
液压混合动力系统的结构形式大致可分为串联型和并联型。其中串联型液压混合动力系统能够使发动机与汽车传动系统解耦，进而可以大幅提高发动机的操作柔性和使用性能。再者，串联型液压混合动力系统具有更好的提高运输汽车燃油经济性的潜力。基于以上考虑，本文以串联型液压混合动力系统作为研究对象，并针对当前该研究中存在的需要解决的问题，主要从以下几个方面展开研究：
（1）高精度的发动机仿真模型。目前混合动力系统研究中采用的发动机模型普遍将油耗与发动机运行状态视为静态映射，这种方法难以准确估计发动机处于瞬态时的油耗。本文所建立的发动机仿真模型描述了发动机的进气动态和输出力矩动态，并根据发动机电子控制单元的工作方式来修正瞬时油耗。实验结果表明该模型能够精确估计各种情况下的发动机瞬时油耗，并能够准确描述发动机的工作动态。
（2）分层递阶的控制系统结构在串联型液压混合动力系统中的应用。本文所建立了分层递阶的控制系统结构包含两个层级，共三个子控制器。顶层的子控制器即为整个混合动力系统的能量管理策略。底层控制器包含两个子控制器，一个用于控制发动机和与发动机相连的液压泵，另一个用于控制汽车驱动马达和机械制动器。这种控制系统结构使得系统中的全部被控对象和需要特殊考虑的各种特殊情况都能被有效控制和管理。
（3）基于模型预测控制的能量管理策略在串联型液压混合动力系统中的应用以及和其它策略效果的对比。目前混合动力系统能量管理策略种类繁多，根据其发展顺序和特点，大致可分为三类，即基于规则的、基于离线优化的（包括确定型动态规划法、随机动态规划法等）和基于在线优化的（即模型预测控制方法）。其中基于模型预测控制的能量管理策略提出较晚，而且目前该策略在液压混合动力系统中的应用尚未见诸于文献。本文设计并应用了这三种类型中各自最具代表性的能量管理策略，即基于液压储能器荷能状态调节的规则式能量管理策略（Rule Based，RB），基于随机动态规划方法的离线优化式能量管理策略（Stochastic Dynamic Programming，SDP）和基于模型预测控制的在线优化式能量管理策略（Model Predictive Control，MPC），并分别研究其特点和应用效果。结果表明无论从提高燃油经济性还是从改善汽车动力性来说，MPC>SDP>RB（“>”表示“优于”的意思）。其中MPC能充分挖掘该串联型液压混合动力系统的潜力。
（4）实时寻优算法研究。在线寻优计算的实时性是基于模型预测控制的能量管理策略在应用中需要解决的主要问题。本文针对性地提出基于李雅普诺夫方法的实时寻优方法，该方法相比于常用的二次规划法，不仅具有更好的实时性，而且计算时间随优化变量个数的增加仅线性增加。此外，该方法具有和二次规划法相当的计算稳定性。
The challenge of improving fuel economy and reducing emission provides strongimpetus for pursuing ultra-efficient vehicle concept. In recent years, fuel consumed bytrucks grows faster, this is a consequence of an increase in the relative number of trucks,as well as higher demand for transportation of goods. As a result, truck systems callfor significantly improved fuel efficiency and hybridization of trucks has become nec-essary. The hydraulic pumps and motors are characterized by high power density andhigh efficiency, in addition, hydraulic accumulators have the ability to accept both highfrequencies and high rate of charging and discharging. These virtues make hydraulic hy-bridization very attractive in large mass associated trucks, thus hydraulic hybrid vehiclesappear to be one of the most viable technologies with significant potential to reduce fuelconsumption. However, the relatively low power density of the hydraulic accumulatorbrings about a unique control challenge, which makes hydraulic hybridization attractedgreat attention in studies.
Hydraulic hybridization of vehicle opens up many possibilities related to systemarchitecture, which can be classified into two broad categories, series or parallel. Becausethere is no mechanical connection between the engine and the wheels in series system, fullflexibility in engine operation can be allowed. Furthermore, with the potential of furtherimproving vehicle fuel economy, hydraulic hybrid vehicle with the series architecture(i.e. Series Hydraulic Hybrid Vehicle, SHHV) is the object of this research. In this paper,research was conducted with respect to some deficiencies which currently exit within thecontext of SHHV studies.
(1) High fidelity engine model. One of the most common methodologies used withinthe context of hybrid powertrain system models considers a purely static approach to es-timate the engine fueling. A steady state fueling map is used to estimate the engine fuelconsumption at different engine operating conditions. Even though this approach givesa satisfactory estimate of the fueling in steady state conditions, large discrepancies areobserved when the engine operates in transient conditions. The engine model developedin this paper focus on a simplified description of the air handling system dynamics inorder to estimate the real air mass flow rate in transient conditions. Similarly, the engine in-cylinder processes which lead to the torque production are described in a simplifiedway and only the low frequency bandwidth dynamics due to torque request variations aredescribed. The final estimation of the fuel mass flow rate is the result of the combinationof a map-based fuel mass flow rate to which a set of corrections accounting for specificphenomena are fully taken into consideration. The approach mimics the actual operationof an ECU (Electric Control Unite) algorithm. Comparison between engine model simu-lation results and experimental data demonstrated the high fidelity property of this enginemodel.
(2) Design and application of hierarchical control architecture in SHHV system. Thehierarchical control architecture developed in this work includes two levels and threesub-module controllers. There is one top level controller, which is the vehicle powermanagement policy. There are two low level sub-module controller, one manages theengine and its associated hydraulic pump/motor, the other one operate the vehicle drivingmotors and the mechanical brakes. This architecture allows all the control variables andspecific phenomena in this SHHV system can properly managed.
(3) Application of model predictive control based power management strategy andits comparison with other power management strategies. There is a rich literature on thepower management strategy study, which can be classified into three broad categories,i.e. rule based strategies, strategies with off-line optimization (e.g. deterministic dynamicprogramming, stochastic dynamic programming, etc.) and strategies with on-line opti-mization (i.e. model predictive control based strategies). In this research, three powermanagement strategies that are typical in their respective categories are developed andthoroughly studied. The three different strategies are thermostatic SoC (of rule based cat-egory, denoted with RB), stochastic dynamic programming based (of the category withoff-line optimization, denoted with SDP) and model predictive control based (of the cat-egory with on-line optimization, denoted with MPC). In particular, currently no studyemploying MPC in SHHV exits, and this work is the first instance. Simulation resultson the federal urban driving schedule demonstrate that MPC>SDP>RB (here”>” meas”better than on fuel economy improvement and power performance”), and more precisely,MPC can significantly expand the operational envelope of SHHV.
(4) Real time optimization. One main disadvantage of MPC for application is thatMPC requires on-line real time optimization, which is computational expensive. To over- come this problem, a Lyapunov based dynamic optimization approach is proposed inthis study. Compared with conventional real time optimization methods (typically thequadratic programming approach), this Lyapunov based approach converges faster andneeds fewer computation time. More importantly, the computation time of the Lyapunovbased approach increases linearly with the number of optimization variables. Further-more, its computing stability can be as good as that of quadratic programming.
液压混合动力系统的结构形式大致可分为串联型和并联型。其中串联型液压混合动力系统能够使发动机与汽车传动系统解耦，进而可以大幅提高发动机的操作柔性和使用性能。再者，串联型液压混合动力系统具有更好的提高运输汽车燃油经济性的潜力。基于以上考虑，本文以串联型液压混合动力系统作为研究对象，并针对当前该研究中存在的需要解决的问题，主要从以下几个方面展开研究：
（1）高精度的发动机仿真模型。目前混合动力系统研究中采用的发动机模型普遍将油耗与发动机运行状态视为静态映射，这种方法难以准确估计发动机处于瞬态时的油耗。本文所建立的发动机仿真模型描述了发动机的进气动态和输出力矩动态，并根据发动机电子控制单元的工作方式来修正瞬时油耗。实验结果表明该模型能够精确估计各种情况下的发动机瞬时油耗，并能够准确描述发动机的工作动态。
（2）分层递阶的控制系统结构在串联型液压混合动力系统中的应用。本文所建立了分层递阶的控制系统结构包含两个层级，共三个子控制器。顶层的子控制器即为整个混合动力系统的能量管理策略。底层控制器包含两个子控制器，一个用于控制发动机和与发动机相连的液压泵，另一个用于控制汽车驱动马达和机械制动器。这种控制系统结构使得系统中的全部被控对象和需要特殊考虑的各种特殊情况都能被有效控制和管理。
（3）基于模型预测控制的能量管理策略在串联型液压混合动力系统中的应用以及和其它策略效果的对比。目前混合动力系统能量管理策略种类繁多，根据其发展顺序和特点，大致可分为三类，即基于规则的、基于离线优化的（包括确定型动态规划法、随机动态规划法等）和基于在线优化的（即模型预测控制方法）。其中基于模型预测控制的能量管理策略提出较晚，而且目前该策略在液压混合动力系统中的应用尚未见诸于文献。本文设计并应用了这三种类型中各自最具代表性的能量管理策略，即基于液压储能器荷能状态调节的规则式能量管理策略（Rule Based，RB），基于随机动态规划方法的离线优化式能量管理策略（Stochastic Dynamic Programming，SDP）和基于模型预测控制的在线优化式能量管理策略（Model Predictive Control，MPC），并分别研究其特点和应用效果。结果表明无论从提高燃油经济性还是从改善汽车动力性来说，MPC>SDP>RB（“>”表示“优于”的意思）。其中MPC能充分挖掘该串联型液压混合动力系统的潜力。
（4）实时寻优算法研究。在线寻优计算的实时性是基于模型预测控制的能量管理策略在应用中需要解决的主要问题。本文针对性地提出基于李雅普诺夫方法的实时寻优方法，该方法相比于常用的二次规划法，不仅具有更好的实时性，而且计算时间随优化变量个数的增加仅线性增加。此外，该方法具有和二次规划法相当的计算稳定性。
The challenge of improving fuel economy and reducing emission provides strongimpetus for pursuing ultra-efficient vehicle concept. In recent years, fuel consumed bytrucks grows faster, this is a consequence of an increase in the relative number of trucks,as well as higher demand for transportation of goods. As a result, truck systems callfor significantly improved fuel efficiency and hybridization of trucks has become nec-essary. The hydraulic pumps and motors are characterized by high power density andhigh efficiency, in addition, hydraulic accumulators have the ability to accept both highfrequencies and high rate of charging and discharging. These virtues make hydraulic hy-bridization very attractive in large mass associated trucks, thus hydraulic hybrid vehiclesappear to be one of the most viable technologies with significant potential to reduce fuelconsumption. However, the relatively low power density of the hydraulic accumulatorbrings about a unique control challenge, which makes hydraulic hybridization attractedgreat attention in studies.
Hydraulic hybridization of vehicle opens up many possibilities related to systemarchitecture, which can be classified into two broad categories, series or parallel. Becausethere is no mechanical connection between the engine and the wheels in series system, fullflexibility in engine operation can be allowed. Furthermore, with the potential of furtherimproving vehicle fuel economy, hydraulic hybrid vehicle with the series architecture(i.e. Series Hydraulic Hybrid Vehicle, SHHV) is the object of this research. In this paper,research was conducted with respect to some deficiencies which currently exit within thecontext of SHHV studies.
(1) High fidelity engine model. One of the most common methodologies used withinthe context of hybrid powertrain system models considers a purely static approach to es-timate the engine fueling. A steady state fueling map is used to estimate the engine fuelconsumption at different engine operating conditions. Even though this approach givesa satisfactory estimate of the fueling in steady state conditions, large discrepancies areobserved when the engine operates in transient conditions. The engine model developedin this paper focus on a simplified description of the air handling system dynamics inorder to estimate the real air mass flow rate in transient conditions. Similarly, the engine in-cylinder processes which lead to the torque production are described in a simplifiedway and only the low frequency bandwidth dynamics due to torque request variations aredescribed. The final estimation of the fuel mass flow rate is the result of the combinationof a map-based fuel mass flow rate to which a set of corrections accounting for specificphenomena are fully taken into consideration. The approach mimics the actual operationof an ECU (Electric Control Unite) algorithm. Comparison between engine model simu-lation results and experimental data demonstrated the high fidelity property of this enginemodel.
(2) Design and application of hierarchical control architecture in SHHV system. Thehierarchical control architecture developed in this work includes two levels and threesub-module controllers. There is one top level controller, which is the vehicle powermanagement policy. There are two low level sub-module controller, one manages theengine and its associated hydraulic pump/motor, the other one operate the vehicle drivingmotors and the mechanical brakes. This architecture allows all the control variables andspecific phenomena in this SHHV system can properly managed.
(3) Application of model predictive control based power management strategy andits comparison with other power management strategies. There is a rich literature on thepower management strategy study, which can be classified into three broad categories,i.e. rule based strategies, strategies with off-line optimization (e.g. deterministic dynamicprogramming, stochastic dynamic programming, etc.) and strategies with on-line opti-mization (i.e. model predictive control based strategies). In this research, three powermanagement strategies that are typical in their respective categories are developed andthoroughly studied. The three different strategies are thermostatic SoC (of rule based cat-egory, denoted with RB), stochastic dynamic programming based (of the category withoff-line optimization, denoted with SDP) and model predictive control based (of the cat-egory with on-line optimization, denoted with MPC). In particular, currently no studyemploying MPC in SHHV exits, and this work is the first instance. Simulation resultson the federal urban driving schedule demonstrate that MPC>SDP>RB (here”>” meas”better than on fuel economy improvement and power performance”), and more precisely,MPC can significantly expand the operational envelope of SHHV.
(4) Real time optimization. One main disadvantage of MPC for application is thatMPC requires on-line real time optimization, which is computational expensive. To over- come this problem, a Lyapunov based dynamic optimization approach is proposed inthis study. Compared with conventional real time optimization methods (typically thequadratic programming approach), this Lyapunov based approach converges faster andneeds fewer computation time. More importantly, the computation time of the Lyapunovbased approach increases linearly with the number of optimization variables. Further-more, its computing stability can be as good as that of quadratic programming.
引文
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