Hybrid bus energy management method

Abstract

The invention discloses a hybrid bus energy management method, which comprises the following steps of: acquiring a speed transition probability model according to historical data of a bus on the same line, current speed information and bus position information by a bus control unit, then estimating the speed, and optimizing energy distribution of the hybrid bus in a prediction zone according to the estimated speed to acquire current optimal power distribution ratio of a fuel oil engine to a motor; and finally determining the actual oil injection quantity and the power provided by the motor, and sending message to a motor control unit and an engine control unit through a controller area network (CAN) bus. Energy management of the hybrid bus is optimized by fully using the characteristics of the bus on the same line; and the method has the characteristics of reasonable energy distribution, high economical efficiency of fuel oil, low exhaust emission, high robustness, energy conservation and environment friendliness.

Description

technical field [0001] The invention relates to the technical field of hybrid power management and control, in particular to a hybrid power bus energy management method. Background technique [0002] The development of the automobile industry is accompanied by the problems of environmental pollution and energy shortage. In order to alleviate these problems, new energy vehicles are an effective way. Since many technologies related to pure electric vehicles are immature, and have bottlenecks such as battery energy density and large capacitor safety, it is too early to promote them. Hybrid electric vehicle (HEV) can be designed based on existing fuel vehicles, so it is more practical. This patent is mainly launched around the hybrid vehicle. Hybrid vehicles use at least two power sources, so the engine can work in a better working range to achieve the goals of reducing fuel consumption, reducing pollutant emissions, and recycling braking kinetic energy. [0003] As the main...

AI Technical Summary

Problems solved by technology

However, this strategy is not universal, and the control effect can only be achieved when the bus operates exactly according to the model trajectory

But the actual situation is that the operation of the bus is very random, and it hardly moves according to the trajectory of the customized strategy, and the time consumption is different each time. If the control strategy is based on a fixed model, it is likely that it will not be able to achieve the expected Control effect

Some researchers have built a stochastic model for the operating conditions of the vehicle, and then used stochastic dynamic programming to solve it. Due to the time complexity of the calculation, it is not suitable for optimization in real-time vehicle operation.

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