Intelligent Energy Management Based on Predictive Control System of PHEV
Chen Xin, Xue Jianbo （ Schaeffler Trading (Shanghai) Co., Ltd., Shanghai 201804） Abstract Rule- based energy management strategy used on Plug- in Hybrid Electric Vehicles (PHEV) has its innate【 】disadvantage that the whole hybrid powertrain system has no choice but to reserve capacity as redundancy to response to the unpredictable driver behaviors in the near future, which could lead to non- optimal system efficiency as expected. This paper focuses on the optimization based algorithm for energy management and economic driving over a pre- selected horizon using messages from Intelligent Traffic System (ITS), which is proposed to schedule the charging or discharging of the high voltage battery, and when to turn on/off the engine and drive electrically. The benefits of the proposed predictive intelligent control strategy are shown by simulations with data extracted from mega city driving situation in Shanghai. Key words: PHEV, Energy management strategy, Predictive intelligent control, ITS, Fuel economy基于预测控制的插电式混合动力汽车智能能量管理（英文） 陈鑫 薛剑波（舍弗勒贸易（上海）有限公司，上海 201804）【摘要】为解决基于规则的插电式混合动力汽车（ PHEV）能量管理策略必须保留混合动力系统容量冗余以应对不可预测的驾驶员行为，从而影响系统效率的问题，研究了基于优化的智能交通系统（ ITS）能量管理和经济行驶算法，利用ITS提供的信息对高压电池的充、放电以及发动机的起动和关闭进行控制，利用上海市行驶工况数据进行了仿真，表明了该控制策略的有效性。主题词：插电式混合动力汽车 能量管理策略 智能预测控制 智能交通系统 燃油经济性中图分类号： U461 文献标识码： A DOI: 10.19620/j.cnki.1000-3703.20181114
The hybrid vehicle is one of the key solutions for increasing fuel economy and reducing greenhouse gas emission in automotive industry. Usually, the hybrid powertrain system is the hybrid of an Internal Combustion Engine (ICE), which has a smaller size but runs more efficiently, and an Electrical Motor (EM), which has the capability to shift the ICE load condition and recuperate the braking energy, and battery system. The opportunity for using different prime movers to satisfy the power demand allows the supervisory control to choose the energy flow between ICE and battery that maximizes global energy efficiency. In general, the fuel economy of a hybrid vehicle is much better than a vehicle with a conventional powertrain.
The modern Intelligent Traffic System (ITS) is based on advanced telematics, wireless connectivity and Global Position System (GPS). The value such information and preview can significantly enhance the energy efficiency of vehicles. For example, this information complements exists in vehicle navigation systems and help drivers in making better route choices to save traveling time and avoid traffic jams. The connection of these information systems and vehicle control system provides the opportunity to incorporate more environmental information than ever before into hybrid vehicle energy management.
In the energy management problem of hybrid
vehicles, battery State Of Charge (SOC) is an important state parameter in determining the optimal power split ratio between ICE and battery. The SOC drops during the
Charge Depleting (CD) operating distance as the vehicle drives electrically without assistance from the ICE. Once reaching the Charge Sustaining (CS) of SOC level, the SOC remains roughly steady while the ICE and the EM work together during CS operation. This strategy emphasizes that during CD operation, the EM satisfies the full vehicle power demand, and the ICE remains off. When the entire mission is known, optimization algorithms such as dynamic CD/CS programming can be used to find the optimal power split ratio.
The estimation of future driving conditions on a sliding window will become possible with improvements of ITS, which give more information about the velocity profile that enabled from traffic data, to vehicle control system. It provides an opportunity to develop an optimal energy management strategy, the control strategy estimates future power demand with a vehicle model and then uses dynamic programming on this estimation. In this paper, a predictive control strategy based on SOC pre-planning task under time-varying traffic conditions that have great value in motion planning of vehicles for fuel saving is considered.
2 Vehicle Model 2.1 Dedicated Hybrid Transmission
The hybrid vehicle studied uses a Dedicated Hybrid Transmission (DHT) as shown in Figure 1. Basically, with the realization of a DHT, the mechanical effort can be reduced potentially through an intelligent use of EMs. In this paper, a DHT concept merges the input power of an ICE and two EMs input shaft electric motor (EM1) and
– output shaft electric motor (EM2). Each of these power units are connected to the drivetrain with 4 gear ratios. One dry multiple disc clutch connects and disconnects the ICE to / from EM1. Modes shown in Table 1 can be driven with the dedicated hybrid transmission.
The dual-motors DHT structure enhances power passing through the high efficiency mechanical path, thereby improving the global efficiency of the powertrain. 2.2 Vehicle Parameters
In this paper, the model for Plug-in Hybrid Electric Vehicle (PHEV) with front wheel drive is used. The
2.3 Longitudinal Dynamics
Here only the quasi-static torque states are analyzed for vehicle dynamics modeling requirement, which means the engine start/stop phases focusing on clutch torque control will be ignored. The disconnect clutch is considered to be naturally completely closed. The relationship between main components torque are shown in Figure 3.