Predictive Optimization of Energy Management Strategy for New Type Power-Split Hybrid Driveline System

doi:10.7652/xjtuxb201901007

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Predictive Optimization of Energy Management Strategy for New Type Power-Split Hybrid Driveline System

更新时间：2025-07-09

- Predictive Optimization of Energy Management Strategy for New Type Power-Split Hybrid Driveline System
- Vol. 53, Issue 1, Pages: 52-61+85(2019)
- 作者机构：
  
  同济大学新能源汽车工程中心,上海,201804
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb201901007
  CLC： U469.72
- Online First：10 January 2019，
  
  Published：2019
- 稿件说明：
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Predictive Optimization of Energy Management Strategy for New Type Power-Split Hybrid Driveline System[J]. 2019, 53(1): 52-61+85.
DOI：

Predictive Optimization of Energy Management Strategy for New Type Power-Split Hybrid Driveline System[J]. 2019, 53(1): 52-61+85. DOI： 10.7652/xjtuxb201901007.

摘要

针对新型双模功率分流混合动力系统

为改善拟搭载样车的能量经济性

开发了基于模型预测控制的实时优化能量管理策略并进行了仿真验证。通过分析各动力源在不同工作模式下的转速转矩关系

建立了功率分流系统模型。通过分析该构型方案在不同功率分流模式下的机械点

得到系统效率随传动比的变化关系

并基于发动机稳态燃油消耗特性曲线建立了其数学模型

基于安时积分法建立了动力电池一阶等效模型。根据已有的发动机模型及动力电池模型

建立了功率分流混合动力系统短时域预测模型

预测了有限时域内电池荷电状态及发动机燃油消耗率的变化。最后

基于预测时域内等效燃油消耗最小提出系统在混合动力模式下发动机工作点的最优决策律

并基于该最优决策律开发功率分流混合动力系统模型预测能量管理策略

实现了各动力源转矩的实时最优分配。设置预测时域和控制时域均为3 s

新欧洲行驶工况仿真结果表明

该控制策略可实现能量管理的实时滚动优化

其百公里油耗为4.95 L

相比于基于规则能量管理策略下的百公里油耗5.364 L

可提升整车大约7.7%的燃油经济性。

Abstract

To improve the fuel economy of a prototype vehicle with a new type dual-mode power split hybrid driveline system

a real-time optimized energy management strategy based on model predictive control(MPC)was developed and verified. First

the relationship of speed and torque of different power source under every working mode was analyzed

and a model of power split system was built. Then the mechanical points of different power split modes were analyzed

and the relationship between system efficiency and gear ratio was obtained. Based on the fuel consumption characteristic curve of the engine

its mathematical model was established. In the meantime

the first-order RC model of battery based on the amper-hour integral method was built. Further

a short-time prediction model for power split hybrid driveline system based on the engine and battery models was obtained to predict the variation of battery SOC and fuel consumption rate in a predictive horizon. Finally

an optimal decision law about the engine operating point under hybrid mode at the minimum cost of the equivalent fuel consumption was proposed

and an MPC-based energy management strategy based on the optimal decision law was developed to realize the real-time optimal distribution of torque among different power sources. Simulation results show that the MPC-based energy management strategy can achieve the real-time rolling optimization of a hybrid power vehicle consuming 4.95 liters of gasoline per 100 kilometers. Compared with 5.364 liters of gasoline per 100 kilometers under the rule-based energy management

MPC-based energy management can dramatically improve fuel economy by 7.7%.

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references

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