Study On Power Matching And Energy Management Strategy For A Plug-in Hybrid Urban Bus

With the energy crisis and environmental pollution becoming increasingly serious,plug-in hybrid electric vehicles,with advantages of both pure electric vehicles and traditional cars such as low fuel consumption,low emissions,no mileage restrictions,was concerned widely.That is considered to be the ideal transition of traditional cars to pure electric vehicles.Because of its fixed running line,frequent idling and start conditions,city bus is more suitable for plug-in hybrid technology.With plug-in hybrid electric urban bus as the object of the Study,this thesis is carried on parameter matching of power system and design/improvement of energy management strategy.According to the vehicle parameters and power design requirements,non-transmission box hybrid system configuration scheme is determined based on the characteristics of China city bus cycle.The energy flow between each components is analyzed and described in detail under each potential working mode.On this basis,the vehicle power demand is estimated and each power component is matched and selected including engine,motor,ISG,battery and final drive.On the basis of following the plug-in hybrid vehicle energy management strategy principles,rule-based hierarchical dynamic logic threshold energy management strategy is proposed based on battery SOC and target velocity.In the light of driving state,that is divided into driving mode and braking mode.Driving mode is divided into electric vehicle,charge depleting and charge sustaining according to battery SOC.Each stage is graded by vehicle velocity.At each sub-mode,power splitting between the power resource is determined by the fundamental of the minimum equivalent gas consumption and maximum economic efficiency.The power model and economic model are built based on GT-Drive.At the same time,the result of powertrain parameter matching and energy management strategy are verified.The results show that the drive performance meets the design requirements,and the power allocation of the energy management strategy is in accordance with the expected.In the economic aspect,under the condition of running a single CCBC,the EV mode,CD mode and CS mode increase by 53.2%,43.8%and 28.6%respectively compared with the traditional natural gas bus while the economic efficiency increase by 33.2%under the condition of running 20 consequent CCBC.Finally,the economic model was verified through the vehicle drum test.And the results show that the error is acceptable.At last,on the basis of the principle of real-valued genetic algorithm,the elite retention strategy and the crossover probability and mutation probability of adaptive change with the number of iterations are introduced which improves the convergence rate and can effectively avoiding the genetic algorithm into local optimum.The algorithm is applied to the energy management parameter optimization problem.Simulink bridge genetic algorithm and GT model information communication while vehicle simulation model as the fitness function solver and the equivalent fuel economy as the optimization target to optimize the control parameters.The optimization results show that,the optimized parameter economy is improved by 6.5%compared with the control parameters derived from engineering experience.What's more,the optimized solution set provides multiple solutions.