Parallel Hybrid Electric Vehicle Energy Management Strategy Optimization
With global energy and environmental issues have become increasingly prominent, the development of low fuel consumption, low emissions of new cars become the primary task of the development of todays automotive industry. In this context, the integration of traditional fuel vehicles and pure electric vehicles advantages hybrid cars become the most promising low emission, low power cars.
Much energy as a new source of transportation, hybrid vehicles used in the performance of its energy management strategy are closely related. Meet the dynamic performance of the car, under the premise energy management strategy should be according to the characteristics of automotive power systems and real time operating conditions, to achieve in the engine, the motor torque distribution between the rational, to get maximum fuel economy performance of the vehicle, Low emissions and smooth driving performance. Hybrid vehicle energy management problem is a nonlinear dynamic optimization involves an important issue that affect vehicle performance and as a hybrid of the industrialization process of a major bottleneck, so far have not been finally resolved, need to overcome.
Because the hybrid system is an integrated electrical, mechanical, chemical and thermodynamic systems of nonlinear dynamic system, itself and its coordination between the various components is extremely complex, difficult to establish precise mathematical model system; while the vehicle driving conditions and the randomness of pilot operation, which also increases the difficulty of designing energy management strategy. In this paper, a parallel hybrid car for several major problems of energy management strategy, combining fuzzy control technology, neural networks, clustering algorithms, multi objective optimization and other related knowledge further study and optimize and improve , the main work is as follows: First introduced topic background, the current development of hybrid vehicles and its key technologies, highlighting the hybrid vehicle energy management strategy research status, energy management strategy for the problems that the energy management strategy optimization and improvement is to improve the performance of key hybrid cars.
Analysis of the parallel hybrid vehicle operating mode and its energy management strategies to control thoughts, then one configuration for metal belt type continuously variable transmission CVT for parallel hybrid vehicles to engine efficiency graphs and battery charge Discharge resistance curve as the main basis, we propose a method based on dynamic logic threshold energy management strategy. By setting a variable threshold parameter, based on real time vehicle parameters to achieve a hybrid system for different operating modes switching, and to determine the different operating modes of the main components in the power system optimum operating curve reasonable control transfer between the engine and the motor torque distribution and the CVT speed ratio, thereby improving vehicle performance.
Instantaneous optimization of traditional energy management strategy were analyzed to determine the impact of the energy distribution of the four main factors that will optimize energy management strategy instantaneous sum for a group of four input single output energy management rules. Then the fuzzy C means clustering for offline simulation to get the energy management rules are classified as samples to train BP neural network, the establishment of energy management for neural network controller, which is proposed based on BP neural network parallel hybrid cars real energy management strategy. Simulation results show that, based on neural networks, real time energy management strategy can effectively reduce fuel consumption, but also significantly improves the energy management in real time.
For parallel hybrid vehicle is widely used fuzzy energy management strategy a number of problems were further research, we propose a fuzzy particle swarm optimization based energy management strategy. First, the establishment of a hybrid powertrain torque demand and batteries state of charge SOC as input, engine torque command output fuzzy controller for hybrid system energy distribution, and the fuzzy interfaces, database, rule base and Sharpen interface design work for analysis and gives a reasonable solution.
Then for the membership function of the fuzzy controller and fuzzy control rules rely mainly on the selection of expert experience, with greater subjectivity and other defects, using particle swarm optimization fuzzy controller fuzzy membership function parameters and control rules. Finally, the simulation experiment shows that PSO based fuzzy energy management strategies and non optimized fuzzy energy management strategy, compared to more effectively reduce fuel consumption, and can well control the battery pack SOC changes.
Parallel Hybrid Electric Vehicle Energy Management Strategy Optimization
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