Research On The Power Management Strategies For A Series Hydraulic Hybrid Vehicle

Currently, the energy issue is one of the key factors restricting the sustainable devel-opment of society, new energy vehicles has become a national development strategy tosolve our energy and environmental issues. Hydraulic hybrid vehicles (HHV) as a new en-ergy vehicles, gradually causes highly valued from governments, research institutions andmajor car manufacturers because of its merits which improve the fuel economy and loweremissions.In order to improve the current energy shortage and environmental pollution situationof China, Taking a medium-sized trucks for the study, in order to improve its fuel economyand dynamic performance, we will have a in-depth studies of the following aspects for theseries hydraulic hybrid vehicles (SHHV) system:1. A forward-facing closed-loop simulation model based on physical features is estab-lished in the Matlab/Simulink environment. Then, in this dissertation, we will applied hi-errchical control architecture which allows all the control variables and specific phenomenain this SHHV system can properly manage. The hierarchical control architecture developedin this work includes two levels. One is the top level controller which is the vehicle powermanagement policy, another is a low level, which operate the engine throttle and the hy-draulic pump/motor. It provides necessary simulation platform for the developmnt of con-trol strategy.2. Introduced a implementable rule-based SOC power management control strategy.As the hydraulic accumulator low energy density, it is easy to cause frequent switching ofthe engine operation state. By considering the influence of engine ON/OFF, the duty of e n-gine ON, FE improvement and vehicle speed error,selection the value of SOCstartand SOC-stop, the simulation results demonstrate that a series hydraulic hybrid vehicle with the pr o-posed rule-based power management control strategy results in fuel econmy increases of12.3%and3.2%over the conventional baseline respectively over FUDS and FHDS.3. An intelligent power management control strategy incorporating artificial neural network and dynamic programming algorithm applied to series hydraulic hybrid propulsionsystem is presented. Based on the parameters of FUDS and FHDS, at the first of all, we usethe artificial neural networks (ANNs) time series forecasting to predict the speed; then us-ing dynamic programming (DP) method, established a series hydraulic hybrid vehicles statevariables, the objective function and constraints, and with the energy management controlstrategy based on the ANNs and DP. Compared with conventional baseline, the engine andthe accumulator to achieve the optimal energy distribution, the simulation results demon-strate fuel economy increase of16.1%and5.9%respectively over FUDS and FHDS.4. Proposed a mixed power management control strategy incorporating ANNs&DPand rule-based approach to obtain a practicable near-optimal contral strategy. By setting thespeed deviation to determine which controller work. The control strategy taking into ac-count the advantages of rule-based energy management strategy and dynamic performanceadvantages of ANNs and DP energy management strategy of economic nature.The simula-tion results demonstrate that a series hydraulic hybrid vehicle with the mixed power man-agement control strategy results in fuel econmy increases of15.5%and4.5%over the con-ventional baseline respectively over FUDS and FHDS. Its vehicle dynamic performance isbetween RB and ANNs&DP, the control strategy can be used as option series hybrid vehi-cle energy management strategies for operation of the vehicle to provide more options atthe other circular pattern.