Study On The Control Strategy Of Parallel Hybrid Vehicles Based On The Road Pattern Identification

Environmental pollution and energy crisis are growing nowadays, and energy saving and environment protecting have been the developing trend of vehicle industry. The hybrid vehicles therefore has become one focal field in developing, for its well performance in energy saving. Control strategy, as the core of hybrid technology, has a direct affect on the energy saving effects. We summarized the feature of different control strategies. On account of traditional rule based control strategy, this paper conducted a further research in different road features and the relevant hybrid energy management strategies, with the idea "matching system, simulating and setting up the model, designing and optimizing the control strategy" The paper proposed a set of hybrid drive control strategies based on road pattern recognition, which enhanced the road condition adaptability of traditional rule based control strategy. The main works are as follows.Firs of all, according to the requirement of vehicle performance, we matched the parameters of the power assembly. A simulation model was built up by PSAT to calculate the maximum speed, acceleration time and fuel consumption. Comparing the results the powertrain matching scheme was worked out, which not only meets the need of dynamic and economy target, but also conforms to reality as well.As a result we proposed a systematic method for parallel hybrid powertrain matching.Secondly in the environment of Matlab/Simulink, the paper set up a forward hybrid bus simulation model, including driver model, controller model and vehicle model(engine model, motor model, battery model, transmission system model, cockpit model). By analyzing the driving condition of the vehicles in the real world, we proposed a rule based control strategy which can not only reduce the fuel consumption significantly but also meet the dynamic performance. The model is verificated by the hybrid powertrain test bench for the precision requirement, as a good support for optimizing of the strategy. Then we extracted the characteristic parameters from several standerd driving cycles such as EUDC, UDDS, New York Bus, Manhattan, CCBC. By the method of statistics, we undertook the cluster analysis to analyse the speed rank and the oscillation of speed and got the road types that can be representative for the vehicle driving condition. A database of different dynamic features was built up from the cluster result.We optimized the control strategies under different road conditions by changing the engine start power and limiting the engine performing area, and got the optimal strategies apply to different road patterns. Combined with the basis of rule based control strategy and the identification of the driving patterns, an optimised strategy which can apply to different road styles is proposed.Finally by means of Bayes theory to identify the real driving patterns, and applying the corresponding optimised control strategies, the simulating results indicate that this suit of strategies can reduce the fuel consumption effectively, and have good adaptability.