Hydraulic Hybrid System Research Articles

Torque control strategy for a parallel hydraulic hybrid vehicle

Hydraulic hybrid system is an important branch of hybrid technology, which has the advantage of high power density and the ability to accept the high rates/high frequencies of charging and discharging, therefore hydraulic hybrid technology is well suited for off-road vehicles and heavy-duty trucks. Relatively lower energy density and complicated coordinating operation between two power sources require a special energy control strategy to maximize the fuel saving potential. This paper presents a new configuration of parallel hydraulic hybrid vehicle (PHHV) to improve the braking energy regenerated potential and engine work efficiency. Based on the analysis of optimal energy distribution for the proposed PHHV over a representative urban driving cycle, a fuzzy torque control strategy based on the vehicle load changes is developed to real-time control the energy distribution for the proposed PHHV. Simulation results demonstrate that the proposed PHHV with torque control strategy takes advantage of the high power density and efficiency characteristics of the hydraulic hybrid system, minimizes the disadvantages of low energy density and effectively improves the fuel economy of PHHV.

Low-Cost Pathway to Ultra Efficient City Car: Series Hydraulic Hybrid System with Optimized Supervisory Control

A series hydraulic hybrid concept (SHHV) has been explored as a potential pathway to an ultra-efficient city vehicle. Intended markets would be congested metropolitan areas, particularly in developing countries. The target fuel economy was ~100 mpg or 2.4 l/100km in city driving. Such an ambitious target requires multiple measures, i.e. low mass, favorable aerodynamics and ultra-efficient powertrain. The series hydraulic hybrid powertrain has been designed and analyzed for the selected light and aerodynamic platform with the expectation that (i) series configuration will maximize opportunities for regeneration and optimization of engine operation, (ii) inherent high power density of hydraulic propulsion and storage components will yield small, lowcost components, and (iii) high efficiency and high power limits for accumulator charging/discharging will enable very effective regeneration. The simulation study focused on the SHHV supervisory control development, to address the challenge of the low storage capacity of the accumulator. Two approaches were pursued, i.e. the thermostatic SOC control, and Stochastic Dynamic Programming for horizon optimization. The stochastic dynamic programming was setup using a set of naturalistic driving schedules, recorded in normal traffic. The analysis included additional degree of freedom, as the engine power demand was split into two variables, namely engine torque and speed. The results represent a significant departure from the conventional wisdom of operating the engine near its “sweet spot” and indicate what is preferred from the system stand-point. Predicted fuel economy over the EPA city schedule is ~93 mpg with engine idling, and ~110 mpg with engine shutdowns.

NLPQL of control rules for improving fuel economy of a parallel hydraulic hybrid bus

Hydraulic hybrid system can improve fuel economy significantly of conventional buses over an urban bus driving cycle. In this paper, a parallel hydraulic hybrid bus (PHHB) and the based traditional bus are modelled and simulated in AMESim, an advanced modelling environment. Over one simplified bus-driving cycle, fuel economy of PHHB is compared with the based conventional bus in simulation and in real road tests. On real road testing fuel economy of PHHB is tested improved by 28% compared to the traditional bus in SMVIC, the National Center of Supervision and Inspection on Motor Products Quality in Shanghai. The model is validated that the approximate improvement ratio of fuel economy is 30% by simulation results. The applied control rules, involving certain variables, are selected by engineering intuition not to fully explore the potential of improvement of fuel economy. Hence, for further improvement of fuel economy of buses, non-linear programming by quadratic Lagrangian (NLPQL) is applied to optimising control rules. Optimal results indicate that improvement can be obtained more than 40% of fuel economy of PHHB compared to the traditional bus over the typical urban bus cycle data in China, the represented driving cycle being more applicable.

Force control for hydraulic load simulator using self-tuning grey predictor – fuzzy PID

Hydraulic systems play an important role in modern industry for the reason that hydraulic actuator systems have many advantages over other technologies with electric motors, as they possess high durability and the ability to produce large forces at high speeds. Therefore, the hydraulic actuator has a wide range of application fields such as hydraulic punching, riveting, pressing machines, and molding technology, where controlled forces or pressures with high accuracy and fast response are the most significant demands. Consequently, many hybrid actuator models have been developed for studying how to control forces or pressures with best results. This paper presents a kind of hydraulic load simulator for conducting performance and stability testing related to the force control problem of hydraulic hybrid systems. In the dynamic loading process, perturbation decreases control performance such as stability, frequency response, and loading sensitivity decreasing or bad. In order to improve the control quality of the loading system while eliminating or reducing the disturbance, a grey prediction model combined with a fuzzy PID controller is suggested. Furthermore, fuzzy controllers and a tuning algorithm are used to change the grey step size in order to improve the control quality. The grey prediction compensator can improve the system settle time and overshoot problems. Simulations and experiments on the hydraulic load simulator are carried out to evaluate the effectiveness of the proposed control method when applied to hydraulic systems with various external disturbances encountered in real working conditions.

Online self-tuning fuzzy proportional—integral—derivative control for hydraulic load simulator

Hydraulic systems play an important role in modern industry owing to the fact that hydraulic actuator systems have many advantages over other technologies with electric motors, high durability, and the ability to produce large force at high speeds. Therefore, the hydraulic actuator has a wide range of application fields such as hydraulic pressing machines, moulding technology, etc. where controlled forces or pressures with high accuracy and fast response are the most significant demands. Consequently, many hybrid actuator models have been developed for research on how to control forces or pressures with the best results. The current paper presents a new kind of hydraulic load simulator for conducting performance and stability tests for control forces of hydraulic hybrid systems. In the dynamic loading process, disturbance makes the control performance (such as stability, frequency response, loading sensitivity, etc.) decrease or turn bad. In order to improve the control performance of a loading system and to eliminate or reduce the disturbance, an online self-tuning fuzzy proportional—integral—derivative (PID) controller is designed. Experiments are carried out to evaluate the effectiveness of the proposed control method applied for hydraulic systems with varied external disturbance as in real working conditions.

A Study on Hydraulic Load Simulator Using Self Tuning Grey Predictor – Fuzzy PID

Nowadays, considering the development of the industry, hydraulic actuator has a wide range of application fields. This paper presents a kind of hydraulic load simulator for conducting performance and stability test for control force of hydraulic hybrid systems. A grey prediction model GM(1,1) combined with a fuzzy PID controller is suggested to apply for this system. Furthermore, fuzzy controllers and a tuning algorithm are used to change the Grey step size to improve the control quality. The grey prediction compensator can improve the system settle time and overshoot problems. Simulations and experiments are carried out to evaluate the effectiveness of the proposed control method applied for hydraulic systems with varied external disturbance as in real working conditions.