Optimal Energy Use in a Light Weight Hydraulic Hybrid Passenger Vehicle

2012 ◽  
Vol 134 (4) ◽  
Author(s):  
Timothy O. Deppen ◽  
Andrew G. Alleyne ◽  
Kim A. Stelson ◽  
Jonathan J. Meyer
Keyword(s):  
Predictive Control ◽  
Control Strategy ◽  
Management Strategy ◽  
Energy Use ◽  
Individual Component ◽  
Light Weight ◽  
Passenger Vehicle ◽  
Energy Management Strategy ◽  
Hybrid Powertrain ◽  
Hydraulic Hybrid

In this study we present a procedure for the design and implementation of a control strategy to optimize energy use within a light weight hydraulic hybrid passenger vehicle. The hydraulic hybrid utilizes a high pressure accumulator for energy storage which has superior power density than conventional battery technology. This makes fluid power attractive for urban driving applications in which there are frequent starts and stops and large startup power demands. A dynamic model of a series hydraulic hybrid powertrain is presented along with the design of a model predictive control based energy management strategy. Model predictive control was chosen for this study because it uses no future information about the drive cycle in its design. This increases the flexibility of the controller allowing it to be directly applied to a variety of drive cycles. Using the model predictive framework, a holistic view of the powertrain was taken in the design of the control strategy, and the impact of each actuator’s efficiency on overall efficiency was evaluated. A hardware-in-the-loop experiment using an electro-hydraulic powertrain testbed was then used to validate the dynamic model and control performance. Through a simulation study in which each actuator’s efficiency was given varying levels of priority in the objective function, it was found that overall system efficiency could be improved by allowing for small sacrifices in individual component performance. In fact, the conventional wisdom of using the additional degrees of freedom within a hybrid powertrain to optimize engine efficiency was found to yield the lowest overall powertrain efficiency. In this work we present a rigorous framework for the design of an energy management strategy. The design method improves the powertrain’s operational efficiency by finding the best balance between optimizing individual component efficiencies. Furthermore, since the design of the control strategy is built upon an analysis of individual components, it can be readily extended to other architectures employing different actuators.

Modeling and Design of a Hydraulic Hybrid Powertrain for Passenger Vehicle

2017 ◽  
Author(s):  
Haoxiang Zhang ◽  
Feng Wang ◽  
Kim A. Stelson
Keyword(s):  
Energy Management ◽  
Management Strategy ◽  
Controller Design ◽  
Mechanical Transmission ◽  
Passenger Vehicle ◽  
Energy Management Strategy ◽  
Hybrid Powertrain ◽  
Hydraulic Hybrid ◽  
Hydraulic Accumulator ◽  
Pressure Controlled

A hydraulic hybrid powertrain for passenger vehicle is studied in this paper. The hydraulic hybrid powertrain consists of a hydro-mechanical transmission and a hydraulic accumulator. The key component of this hydro-mechanical transmission is a pressure-controlled hydraulic transmission. It combines pumping and motoring function in one unit and is potentially more competitive in terms of both energy efficiency and cost effectiveness than a conventional hydrostatic transmission. By feeding the output flow of the pressure-controlled hydraulic transmission to a variable displacement motor coupled to the transmission output shaft, a more compact and simpler hydro-mechanical transmission is constituted. In this paper the systematic approach of applying the hydraulic hybrid powertrain to a passenger vehicle is studied. A dynamic simulation model is developed in Simulink and the U.S. EPA’s urban cycle is used as the test driving cycle. A rule-based energy management strategy (EMS) for the hydraulic hybrid powertrain has also been developed. The system parameter design, controller design and the energy management strategy are evaluated through simulation.

Power Optimization of Series Hydraulic Hybrid Powertrain for Compact Wheel Loader

2019 ◽  
Author(s):  
Qunya Wen ◽  
Feng Wang ◽  
Bing Xu ◽  
Zongxuan Sun
Keyword(s):  
Energy Management ◽  
Fuel Economy ◽  
Management Strategy ◽  
Power Optimization ◽  
Parameter Study ◽  
Energy Management Strategy ◽  
Hybrid Powertrain ◽  
Wheel Loader ◽  
Hydraulic Hybrid ◽  
Equivalent Consumption Minimization Strategy

Abstract As an effective approach to improving the fuel economy of heavy duty vehicles, hydraulic hybrid has shown great potentials in off-road applications. Although the fuel economy improvement is achieved through different hybrid architectures (parallel, series and power split), the energy management strategy is still the key to hydraulic hybrid powertrain. Different optimization methods provide powerful tools for energy management strategy of hybrid powertrain. In this paper a power optimization method based on equivalent consumption minimization strategy has been proposed for a series hydraulic hybrid wheel loader. To show the fuel saving potential of the proposed strategy, the fuel consumption of the hydraulic hybrid wheel loader with equivalent consumption minimization strategy was investigated and compared with the system with a rule-based strategy. The parameter study of the equivalent consumption minimization strategy has also been conducted.

scholarly journals Energy management strategy for a power-split hydraulic hybrid vehicle based on Lagrange multiplier and its modifications

2018 ◽  
Vol 233 (5) ◽  
pp. 511-523 ◽  
Author(s):  
Zhekang Du ◽  
Kai Loon Cheong ◽  
Perry Y Li
Keyword(s):  
Energy Management ◽  
Lagrange Multiplier ◽  
Fuel Economy ◽  
Control Strategy ◽  
Management Strategy ◽  
Storage Capacity ◽  
State Of Charge ◽  
Energy Management Strategy ◽  
Hydraulic Hybrid ◽  
Hydraulic Hybrid Vehicle

Lagrange multiplier approach is a computationally efficient method for computing optimal energy management strategy for a hydraulic hybrid vehicle under the assumption that the accumulator dynamics can be ignored and only the net use of storage energy is considered. Although it provides a close estimate to the fuel economy compared to that obtained using dynamic programming, the resulting control strategy does not respect the physical limits of the storage capacity of the hydraulic accumulator. Thus, the synthesized control strategy is not feasible for actual driving. This article investigates the basic Lagrange multiplier approach for real-time control and proposes modifications so that the storage capacity is respected. It is shown that the Lagrange multiplier can be interpreted as an equivalent loss factor which turns out to be the marginal loss associated with the discharge of stored energy. The two proposed modifications are as follows: (1) a moving horizon approach and (2) making the Lagrange multiplier a function of the current state of charge. Both methods are successful in maintaining the accumulator state of charge within limits with modest effect on fuel economy (3%–5% lower).

A novel hybrid energy management strategy of a diesel-electric hybrid ship based on dynamic programing and model predictive control

2022 ◽  
pp. 147509022110689
Author(s):  
Yupeng Yuan ◽  
Mingshuang Chen ◽  
Jixiang Wang ◽  
Wanneng Yu ◽  
Boyang Shen
Keyword(s):  
Model Predictive Control ◽  
Energy Management ◽  
Predictive Control ◽  
Control Strategy ◽  
Management Strategy ◽  
Energy Management Strategy ◽  
Threshold Control ◽  
Rule Based ◽  
Dynamic Programing ◽  
Simulation Results

The energy-saving characteristics of diesel-electric series hybrid ships largely depend on their energy management strategy. In this paper, a strategy that combines dynamic programing and model predictive control (DP-MPC) is proposed to solve the energy management problems of diesel-electric hybrid ships. The DP-MPC strategy has considered some typical working conditions of a ship, and the corresponding influence of white noise disturbance on the control strategy was studied. The simulation results show that the DP-MPC strategy has an excellent anti-interference capability. The control performance of the DP-MPC strategy is then further analyzed and compared with the rule-based logic threshold control strategy. The simulation results show that the proposed DP-MPC strategy can save 2.5% of the fuel consumption and has a better anti-interference capability than the rule-based control strategy.

scholarly journals Power-Following Control Strategy of a Wheel-Drive Hydraulic Hybrid Vehicle

2020 ◽  
Vol 66 (3) ◽  
pp. 193-202
Author(s):  
Tao Zhang ◽  
Qiang Wang ◽  
Xiao-Hui He ◽  
Si-Sheng Li ◽  
Xin-Min Shen
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Fuel Economy ◽  
Control Strategy ◽  
Management Strategy ◽  
Dynamic Performance ◽  
Energy Management Strategy ◽  
Hydraulic Hybrid ◽  
Wheel Drive ◽  
Critical Technology

Energy management strategy is a critical technology for improving the fuel economy of wheel-drive hydraulic hybrid vehicles. For driving, a power-following control strategy is proposed in this study by adding several working points of the engine in the optimal fuel economy power curve. For braking, the “I” curve distribution strategy based on critical braking strength zmin was adopted. A test bench was constructed according to the quarter of the prototype vehicle. Taking the typical working conditions of Federal Urban Driving Schedule (FUDS) and the selfset extra-urban driving schedule (EUDC-1) cycle condition into consideration, the energy management strategy was studied. The torque and speed of the simulated engine and pressure of the accumulator were obtained. The test fuel consumption in this research was compared with the original fuel consumption of the prototype vehicle. It was found that the proposed energy management strategy could effectively improve the fuel economy by more than 24 % under the requirement of satisfying the dynamic performance of the whole vehicle.

scholarly journals Integration of a Model Predictive Control with a Fast Energy Management Strategy for a Hybrid Powertrain of a Connected and Automated Vehicle

2021 ◽  
Vol 12 (3) ◽  
pp. 159
Author(s):  
Enrico Landolfi ◽  
Francesco Junior Minervini ◽  
Nicola Minervini ◽  
Vincenzo De De Bellis ◽  
Enrica Malfi ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Real Time ◽  
Energy Management ◽  
Predictive Control ◽  
Management Strategy ◽  
Transport Sector ◽  
Energy Management Strategy ◽  
Steering Angle ◽  
Hybrid Powertrain ◽  
The Road

In the years to come, Connected and Automated Vehicles (CAVs) are expected to substantially improve the road safety and environmental impact of the road transport sector. The information from the sensors installed on the vehicle has to be properly integrated with data shared by the road infrastructure (smart road) to realize vehicle control, which preserves traffic safety and fuel/energy efficiency. In this context, the present work proposes a real-time implementation of a control strategy able to handle simultaneously motion and hybrid powertrain controls. This strategy features a cascade of two modules, which were implemented through the model-based design approach in MATLAB/Simulink. The first module is a Model Predictive Control (MPC) suitable for any Hybrid Electric Vehicle (HEV) architecture, acting as a high-level controller featuring an intermediate layer between the vehicle powertrain and the smart road. The MPC handles both the lateral and longitudinal vehicle dynamics, acting on the wheel torque and steering angle at the wheels. It is based on a simplified, but complete ego-vehicle model, embedding multiple functionalities such as an adaptive cruise control, lane keeping system, and emergency electronic brake. The second module is a low-level Energy Management Strategy (EMS) of the powertrain realized by a novel and computationally light approach, which is based on the alternative vehicle driving by either a thermal engine or electric unit, named the Efficient Thermal Electric Skipping Strategy (ETESS). The MPC provides the ETESS with a torque request handled by the EMS module, aiming at minimizing the fuel consumption. The MPC and ETESS ran on the same Microcontroller Unit (MCU), and the methodology was verified and validated by processor-in-the-loop tests on the ST Microelectronics board NUCLEO-H743ZI2, simulating on a PC-host the smart road environment and a car-following scenario. From these tests, the ETESS resulted in being 15-times faster than than the well-assessed Equivalent Consumption Minimization Strategy (ECMS). Furthermore, the execution time of both the ETESS and MPC was lower than the typical CAN cycle time for the torque request and steering angle (10 ms). Thus, the obtained result can pave the way to the implementation of additional real-time control strategies, including decision-making and motion-planning modules (such as path-planning algorithms and eco-driving strategies).

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