Multimode automatic switching method for energy control strategies of extended-range electric vehicle

Abstract

The invention relates to a multimode automatic switching method for energy control strategies of an extended-range electric vehicle . The method comprises the steps as follows: 1) collecting driving condition information of the vehicle in real time, and calculating the characteristic parameters of car vehicle driving conditions in a certain time; 2) conducting matching processing to the characteristic parameters of the current condition in the step 1) and the characteristic parameters of typical conditions, and determining the type of the current driving condition; and 3) automatically selecting the optimal energy control strategy under the type of the condition according to the type of the condition in the step 2), and automatically switching the current energy control strategy into the optimal energy control strategy. Compared with the prior art, the multimode automatic switching method has the advantages of being reliable in performances, stable in whole-vehicle power performance, strong in practicability and the like.

Description

technical field [0001] The invention relates to the technical field of electric vehicle control, in particular to an energy control strategy multi-mode automatic switching method for an extended-range electric vehicle. Background technique [0002] Electric vehicles are considered to be the most potential new energy vehicle technology to solve the energy crisis and environmental pollution. However, pure electric vehicles have the problems of short driving range and long charging time. The emergence of extended-range electric vehicles effectively makes up for this deficiency. [0003] The range-extender electric vehicle is equipped with a range extender that can increase the mileage, and serves as the power source of the vehicle together with the power battery. The range extender is an auxiliary energy device that can generate electricity and charge the on-board power battery, such as fuel cell engines, batteries and internal combustion engine etc. When the battery power is ...

AI Technical Summary

Problems solved by technology

Although this method can take into account a lot of driving state information and realize more complex control rules, the implementation is more complicated. The establishment of the fuzzy controller mainly depends on experience, and it is impossible to obtain the global optimal

[0014] Among the above four energy management strategies and methods, only the thermostat energy management strategy has been popularized and applied, and other strategies and methods are immature and not very practical

At present, in the process of formulating the energy management strategy and method of the whole vehicle, at most the driving state of the whole vehicle is considered, that is, the depth of the accelerator pedal, the braking state, the SOC of the battery and the output power efficiency point of the range extender, etc. The impact of working conditions on the fuel economy of the vehicle, and the formulation of control rules is basically based on experience. Although it is practical to determine the control parameters in the process of trial and error, it cannot optimize the vehicle. Algorithm optimization of control strategy parameters can effectively deal with such problems

[0015] The thermostat control strategy has incomparable advantages over other control strategies, but it is greatly affected by the driving conditions. For a specific driving condition, there is a corresponding optimal control strategy parameter value, but the optimal control strategy for a specific working condition The strategy parameter values ​​may not be able to meet the performance requirements of other working conditions, especially the dynamic performance cannot be guaranteed, so the maximum output power of the range extender that can meet the dynamic requirements of all working conditions is often used, but this reduces the economy of the vehicle , can not achieve the optimum in the entire range of operating conditions, the multi-mode switching control strategy can achieve the optimal in the entire range of driving conditions by switching between different optimal control strategies

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