Ride quality evaluation of the soil compactor cab supplemented by auxiliary hydraulic mounts via simulation and experiment

In order to evaluate the ride quality of the soil compactor cab supplemented by the auxiliary hydraulic mounts (AHM), a nonlinear dynamic model of the soil compactor interacting with the off-road deformable terrain is established based on Matlab/Simulink sofware. The power spectral density (PSD) and the weighted root mean square (RMS) of acceleration responses of the vertical driver s seat, the cab s pitch and roll angle are chosen as objective functions in low-frequency range. Experimental investigation is also used to verify the accuracy of the model. The influence of the damping coefficients of the AHM on the cab s ride quality is analyzed, and damping coefficients are then optimized via a genetic algorithm program. The research results show that the cab s rubber mounts added by the AHM clearly improve the ride quality under various operating conditions. Particularly, with the optimal damping coefficients of the front-end mounts c a 1,2 = 1 500 N · s/m and of the rear-end mounts c a 3,4 =2 335 N · s/m, the weighted RMS values of the driver s seat, the cab s pitch and roll angle are reduced by 22.2%, 18.8%, 58.7%, respectively. Under the condition of the vehicle travelling, with the optimal damping coefficients of c a 1,2 = 1 500 N · s/m and c a 3,4 =1 882 N · s/m, the maximum PSD values of the driver s seat, the cab s pitch and roll angle are clearly decreased by 36.7%, 54.7% and 50.6% under the condition of the vehicle working.

Multi-mode energy management strategy for hydraulic hub-motor auxiliary system based on improved global optimization algorithm

Heavy commercial vehicles equipped with a hydraulic hub-motor auxiliary system(HHMAS)often operate under complex road conditions.Selecting appropriate operating mode and realizing reasonable energy management to match unpredictable road conditions are the keys to the driving performance and fuel economy of HHMAS.Therefore,a multi-mode energy management strategy(MM-EMS)based on improved global optimization algorithm is proposed in this study for HHMAS.First,an improved dynamic programming(DP)algorithm for HHMAS is developed.This improved DP algorithm considers the effect of SOC and vehicle speed,thereby preventing the calculation results from falling into local optimization.This algorithm also reduces the dimension of the control variable data grid,and the calculation time is reduced by 35%without affecting the accuracy.Second,a MM-EMS with hierarchical control is proposed.This strategy extracts the optimal control rules from the results of the improved DP algorithm.Then it divides the system’s operating region into two types,namely,single-mode working region and mixedmode working region.In the single-mode working region,mode switching is realized through fixed thresholds.In the mixedmode working region,a linear quadratic regulator(LQR)is adopted to determine a target mode and realize SOC tracking control.Finally,the designed MM-EMS is verified separately in offline simulation and hardware-in-the-loop(HIL)under actual vehicle test cycles.Simulation results show that the results between HIL and offline simulation are largely coincidence.Besides,in comparison with the engine optimal control strategy,the designed MM-EMS can achieve an approximate optimal control,with oil savings of 3.96%.