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).

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.

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.

Optimal adaptation equivalent factor of energy management strategy for plug-in CVT HEV

2018 ◽  
Vol 233 (4) ◽  
pp. 877-889 ◽  
Author(s):  
Xinyou Lin ◽  
Qigao Feng ◽  
Liping Mo ◽  
Hailin Li
Keyword(s):  
Energy Management ◽  
Fuel Economy ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Adaptation Strategy ◽  
Management Control ◽  
Energy Management Strategy ◽  
Driving Mode ◽  
Driving Cycles ◽  
Equivalent Factor

This study presents an adaptive energy management control strategy developed by optimally adjusting the equivalent factor (EF) in real-time based on driving pattern recognition (DPR), to guarantee the plug-in hybrid electric vehicle (PHEV) can adapt to various driving cycles and different expected trip distances and to further improve the fuel economy performance. First, the optimization model for the EF with the battery state of charge (SOC) and trip distance were developed based on the equivalent consumption minimization strategy (ECMS). Furthermore, a methodology of extracting the globally optimal EF model from genetic algorithm (GA) solution is proposed for the design of the EF adaptation strategy. The EF as the function of trip distances and SOC in various driving cycles is expressed in the form of map that can be applied directly in the corresponding driving cycle. Finally, the algorithm of DPR based on learning vector quantization (LVQ) is established to identify the driving mode and update the optimal EF. Simulation and hardware-in-loop experiments are conducted on synthesis driving cycles to validate the proposed strategy. The results indicate that the optimal adaption EF control strategy will be able to adapt to different expected trip distances and improve the fuel economy performance by up to 13.8% compared to the ECMS with constant EF.

Optimal energy management strategy for fuel cell/battery/supercapacitor vehicles using wavelet transform and equivalent consumption minimization strategy

2021 ◽  
pp. 095440702110697
Author(s):  
Pengfei Zou ◽  
Fazhan Tao ◽  
Zhumu Fu ◽  
Pengju Si ◽  
Chao Ma
Keyword(s):  
Wavelet Transform ◽  
Fuel Cell ◽  
Energy Management ◽  
Fuel Economy ◽  
Management Strategy ◽  
Low Frequency ◽  
Energy Management Strategy ◽  
Power Sources ◽  
Optimal Energy ◽  
Optimal Energy Management

In this paper, the hybrid electric vehicle is equipped with fuel cell/battery/supercapacitor as the research object, the optimal energy management strategy (EMS) is proposed by combining wavelet transform (WT) method and equivalent consumption minimization strategy (ECMS) for reducing hydrogen consumption and prolonging the lifespan of power sources. Firstly, the WT method is employed to separate power demand of vehicles into high-frequency part supplied by supercapacitor and low-frequency part allocated to fuel cell and battery, which can effectively reduce the fluctuation of fuel cell and battery to prolong their lifespan. Then, considering the low-frequency power, the optimal SOC of battery is used to design the equivalent factor of the ECMS method to improve the fuel economy. The proposed hierarchical EMS can realize a trade-off between the lifespan of power sources and fuel economy of vehicles. Finally, the effectiveness of the proposed EMS is verified by ADVISOR, and comparison results are given compared with the traditional ECMS method and ECMS combining the filter.

scholarly journals Multi-objective Parameters Optimization for HEV Based on improved Particle Swarm Algorithm

2019 ◽  
Vol 118 ◽  
pp. 02005
Author(s):  
Ying Ai ◽  
Yuanjie Gao ◽  
dongsheng Liu
Keyword(s):  
Electric Vehicle ◽  
Energy Management ◽  
Fuel Economy ◽  
Management Strategy ◽  
Hybrid Electric Vehicle ◽  
Fuzzy Controller ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Energy Management Strategy ◽  
Multi Objective

Hybrid electric vehicle fuel consumption and emissions are closely related to its energy management strategy. A fuzzy controller of energy management using vehicle torque request and battery state of charge (SOC) as inputs, engine torque as output is designed in this paper foe parallel hybrid electric vehicle. And a multi-objective mathematical function which purpose on maximize fuel economy and minimize emissions is also established, in order to improve the adaptive ability and the control precision of basic fuzzy controller, this paper proposed an improved particle swarm algorithm that based on dynamic learning factor and adaptive inertia weight to optimize the control parameters. Simulation results based on ADVISOR software platform show that the optimized energy management strategy has a better distribution of engine and motor torque, which helps to improved the vehicle’s fuel economy and exhaust emission performance.

Investigation on the Energy Management Strategy for Hydraulic Hybrid Wheel Loaders

2013 ◽  
Author(s):  
Feng Wang ◽  
Mohd Azrin Mohd Zulkefli ◽  
Zongxuan Sun ◽  
Kim A. Stelson
Keyword(s):  
Energy Management ◽  
Hydraulic System ◽  
Management Strategy ◽  
Energy Management Strategy ◽  
Road Vehicles ◽  
Engine Operation ◽  
Wheel Loader ◽  
Hydraulic Hybrid ◽  
Power Split ◽  
Wheel Loaders

Energy management strategies for a hydraulic hybrid wheel loader are studied in this paper. The architecture of the hydraulic hybrid wheel loader is first presented and the differences of the powertrain and the energy management system between on-road vehicles and wheel loaders are identified. Unlike the on-road vehicles where the engine only powers the drivetrain, the engine in a wheel loader powers both the drivetrain and the working hydraulic system. In a non-hybrid wheel loader, the two sub-systems interfere with each other since they share the same engine shaft. By using a power split drivetrain, it not only allows for optimal engine operation and regenerative braking, but also eliminates interferences between driving and working functions, which improve the productivity, fuel efficiency and operability of the wheel loader. An energy management strategy (EMS) based on dynamic programming (DP) is designed to optimize the operation of both the power split drivetrain and the working hydraulic system. A short loading cycle is selected as the duty cycle. The EMS based on DP is compared with a rule-based strategy through simulation.

scholarly journals Real-time Energy Management Strategy for Oil-Electric-Liquid Hybrid System based on Lowest Instantaneous Energy Consumption Cost

Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 784 ◽  
Author(s):  
Yang Yang ◽  
Zhen Zhong ◽  
Fei Wang ◽  
Chunyun Fu ◽  
Junzhang Liao
Keyword(s):  
Global Optimization ◽  
Real Time ◽  
Energy Management ◽  
Management Strategy ◽  
Threshold Energy ◽  
Energy Management Strategy ◽  
Hydraulic Hybrid ◽  
Consumption Cost ◽  
Saving Effect ◽  
Instantaneous Energy

For the oil–electric–hydraulic hybrid power system, a logic threshold energy management strategy based on the optimal working curve is proposed, and the optimal working curve in each mode is determined. A genetic algorithm is used to determine the optimal parameters. For driving conditions, a real-time energy management strategy based on the lowest instantaneous energy cost is proposed. For braking conditions and subject to the European Commission for Europe (ECE) regulations, a braking force distribution strategy based on hydraulic pumps/motors and supplemented by motors is proposed. A global optimization energy management strategy is used to evaluate the strategy. Simulation results show that the strategy can achieve the expected control target and save about 32.14% compared with the fuel consumption cost of the original model 100 km 8 L. Under the New European Driving Cycle (NEDC) working conditions, the energy-saving effect of this strategy is close to that of the global optimization energy management strategy and has obvious cost advantages. The system design and control strategy are validated.

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.

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