Control Strategy Optimization And Dynamic Coordination Control Of Hybrid Electric Bus With AMT

Hybrid electric vehicle control is key technology to optimize vehicle performances.How to reduce vehicle fuel consumption and meet the power demand, these sections havebeen the researchers’ focus. According to the statistic results known a large number ofhybrid electric vehicle related papers are more focused on hybrid control algorithmstudying. In this paper, the steady state hybrid energy management strategies weredivided into three parts of control strategy designing, control rules making, and controlparameters optimization to introduce hybrid powertrain design methods. Meanwhile, thecoordinated control strategies in transient condition were divided into transient modeswitching control and gear-shifting coordinated control, so as to solve the vehicle controlproblems under the steady-state and transient conditions.For the parameters matching problems of hybrid powertrain system, in this paper,power requirement as constraints condition, fuel economy as the optimization objective toselect the best powertrain Map by optimization algorithm, which avoid the shortage ofpower matching for hybrid powertrain. Meanwhile, vehicle simulation model was built,its simulation results were compared with commercial Cruise vehicle model results toensure the subsequent simulation accuracy and reliability.Hybrid powertrain system of the running process is a complex stochastic process, itis difficult to meet the vehicle performance demand with the traditional rule-based designmethodology. For the optimal control problems of hybrid powertrain system, optimizationalgorithms were used in the vehicle control strategy development. Vehicle fuel economyoptimization problem was simplified as the mathematical function optimization problembased on time-history, formulate function goals, constraints, optimization and calculationmethods to obtain the optimal solution. In this paper, instantaneous and globaloptimization methods were provided to solve optimal vehicle control problem, its controland optimization results provides effective evidence for subsequent control rulesextraction.For the control rules problems of hybrid electric vehicle, this paper proposes acontrol rules designing method that combines the advantages of instantaneous and globaloptimization algorithms to extract mode switching rules, gear-shifting rules and torquedistribution rules. According with the hybrid powertrain characteristics to determine thepriorities of gear-shifting control and torque distribution and achieve system integration control, which provide effective guidance for logic threshold control rules designing andprovide the good real-time and stability of control rules for application in real vehicle..Meanwhile, these methods avoid the shortage of traditional design methods that dependon designer experiences and trial and error method takes a lot of time to repeatdebugging.For the control parameters optimization problems of hybrid electric vehicle, in thispaper, iterative optimization method was proposed to encode the optimization parameters,set the parameters areas, optimization goals to obtain the optimal control parameters,which provides a new ideal for the control parameter optimization. These methods solvethe traditional control parameters calibration method time consuming and no theoreticalsupports, the complexity increases exponentially when the control parameter increases.Meanwhile, this paper proposes driving cycle recognition algorithm based on the rollingtime window to update the control parameters and achieve adaptive controlling. Thesemethods avoid the limitations of single control parameter for actual driving cycle.For the problems of hybrid electric vehicle jerking of mode transition and powerinterruption of gear-shifting, this paper provides the coordinated control algorithm ofmode switching to decrease vehicle jerk, and no-clutch shift operation control technologyto avoid the power interruption of transmission gear-shifting.For verifying the performance of offline control algorithm was used in the real-timesystem. In this paper, hardware-in-the-loop simulation system was proposed, dSPACEcontroller as a vehicle environment simulation, TTC200controller as the actual controllerand CAN networks and other structures were building. According with experimentalresults known, vehicle control algorithms have good real-time performance and highfeasibility, providing the prerequisite and guarantee for subsequent verification of theactual vehicle. Finally, test bench experiment was provided for functional verification.