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检索条件"主题词=energy management"

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energy management of a Parallel Plug-In Hybrid Electric Vehicle Based on SA-PSO Algorithm

Energy Management of a Parallel Plug-In Hybrid Electric Vehi...

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第36届中国控制会议

作者： Ping Li Naxin Cui Zhuo Kong Chenghui Zhang School of Control Science and Engineering Shandong University

ISBN: (纸本)9781538629185

In this paper,an intelligent energy management strategy is introduced to improve the fuel economy of a parallel plug-in hybrid electric vehicle（PHEV）.Based on the dynamic system analysis,a fuzzy controller is designed for the energy management of PHEV.Then the combination of Simulated Annealing and Particle Swarm Optimization（SA-PSO） is applied to achieve the optimal parameters of the fuzzy controller.To improve the adaptability of the strategy under different road conditions,the hybrid driving cycle that composed of HWFET,LA92,Ftp75,Jal015 and NEDC driving cycles is taken as the driving cycle for simulation.Moreover,simulations under NEDC and UDDS driving cycles are taken to verify the effects of the proposed energy management strategy.Simulation results indicate that the proposed energy management strategy is effective in improving the fuel economy under different driving conditions.

关键词： Plug-in hybrid electric vehicle energy management fuzzy logic SA-PSO algorithm

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energy management Strategy based on Dynamic Programming Considering Engine Dynamic Operating Conditions Optimization

Energy Management Strategy based on Dynamic Programming Cons...

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第三十九届中国控制会议

作者： Xu Wang Ying Huang Fen Guo Wenqiang Zhao School of Mechanical Engineering Beijing Institute of Technology Beijing Benz Automotive Co. Ltd.

It is known that the hybrid vehicle energy management strategy based on dynamic programming DP can be used as a reference for other strategies. However, usually only fuel consumption of hybrid vehicles is focused on and dynamic conditions of engines are ignored. This research considers a plug-in hybrid electric vehicle as an object, a mathematical model of the vehicle and its energy management strategy based on dynamic programming are developed. The cost function of dynamic programming proposed in this paper not only pays attention to the fuel consumption of the vehicle, but also optimizes the engine start-stop state change and engine speed and torque fluctuation, thus ensuring the engine to work efficiently and have the potential of improving the emission performance. At the same time, entropy-weight method is introduced to determine the weight coefficients of the cost function, so that the determination process is separated from the subjective judgment and is closely linked with objective driving conditions. In addition, aiming at further improvement of DP optimization result when a lager discretization interval is selected for better real-time performance, a method for power deviation compensation is proposed. The simulation results show that the DPbased energy management strategy considering the optimization of engine dynamic operating conditions has a small increase in fuel consumption compared with the traditional DP-based strategy, but it can significantly reduce the dynamic operating conditions of the engine and reduce the fluctuation of engine speed and torque and the frequency of engine start-stop.

关键词： PHEV energy management Dynamic Programming Operating Conditions Optimization

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Distributed Algorithm for Stochastic energy management with Non-convex Constraint

Distributed Algorithm for Stochastic Energy Management with ...

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第40届中国控制会议

作者： Fei Yang Suli Zou Zhongjing Ma School of Automation Beijing Institute of Technology

A predictable distributed algorithm is proposed to solve the stochastic energy management problem of a microgrid system with renewable energy under real-time price schemes. System uncertainties, including wind power and load, are modeled as two-dimension policy-based structure to response from the deviation of the realized and expectation value. Due to the randomness of the uncertainties, a chance constraint on energy balance is considered which allows the mismatch of supply and demand to fluctuate in an acceptable range. The numerical experiments are provided and the effectiveness of the proposed algorithm is analyzed. According to the simulation results, the probabilistic energy balance is guaranteed and the proposed algorithm with two-dimension model has better economic performance or shorter operation time comparing to other algorithms.

关键词： Microgrid system distributed optimization algorithm energy management predictive control

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Logical Stochastic Optimization Approach to energy management of Plug-in Hybrid Electric Vehicle

Logical Stochastic Optimization Approach to Energy Managemen...

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第36届中国控制会议

作者： Jiangyan Zhang Yuhu Wu Tielong Shen Jixiang Fan College of Mechanical and Electronic Engineering Dalian Minzu University School of Control Science and Engineering Dalian University of Technology Department of Engineering and Applied Sciences Sophia University Harbin Normal University School of Physics and Electronic Engineering

ISBN: (纸本)9781538629185

This paper proposes a control scheme for the energy management of plug-in hybrid electric vehicles（HEVs）.Consider the urban driving case,the traffic conditions are treated as stochastic processes of the driver demands.Taking the essential characteristics of plug-in HEVs into account,a logical-based optimization approach is applied to realize the equivalent energy cost minimization of the powertrain.The stochastic design approach provides the solution of a finite horizon optimal control problem.The performance of the proposed control scheme is evaluated by means of a full-scaled hybrid electric vehicle（HEV）simulator.

关键词： Plug-in HEV energy management Logical Control Stochastic Optimal Control

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Reinforcement Learning energy management for Hybrid Electric Tracked Vehicle with Deep Deterministic Policy Gradient

Reinforcement Learning Energy Management for Hybrid Electric...

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2020中国汽车工程学会年会暨展览会

作者： Zhang Bin Wu Jinlong Zou Yuan Zhang Xudong Beijing Institute of Technology

Reinforcement learning（RL） has been applied to energy management of hybrid electric vehicles to synthesize the system efficiency and adaptability.However,the existing RL-based energy management strategies still suffer the "curse of dimensionality"due to the discretization of the state and control action variables.To cure this disadvantage,a continuous RL-based energy management adopting deep deterministic policy gradient（DDPG） is proposed and applied to a series hybrid electric tracked vehicle.First,DDPGbased energy management strategy is put forward,where two sets of neural networks are adopted to parameterize strategy and approximate the action-value function respectively to eliminate the discretization.In addition,an online updating framework of energy management is carried out to increase the adaptability of the energy management strategy.The simulation results show that the fuel consumption of the online updating strategy is 5.9% lower than that of the stationary strategy,and is close to that of dynamic programming benchmark strategy.Besides,the computational burden is significantly reduced and can be implemented in real-time.

关键词： energy management hybrid electric tracked vehicle deep reinforcement learning

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Multi-time Scale Hierarchical Predictive Control for energy management of Microgrid System with Smart Users

Multi-time Scale Hierarchical Predictive Control for Energy ...

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第26届中国控制与决策会议

作者： Jun Xu Yuanyuan Zou Yugang Niu Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China Univ.of Science and Technology Key Laboratory of System Control and Information Processing Ministry of Education

In this paper, a multi-time scale hierarchal model predictive control strategy is proposed to optimize energy management problem of a microgrid with multiple smart users. According to the power flow among different energy modules, a hierarchical system model and a multi-time scale hierarchal energy optimization management problem are established. The centralized controller in the upper layer is to optimize the charge/discharge time and energy of storage devices, controllable supply power adjustment and dispatch of the aggregators. The optimization problem in the lower layer is to meet users’ demands in real time. Meanwhile, in order to improve the disturbances caused by the randomness of renewable energy and variant loads, a multi-time scale optimization scheme is applied. At the slow scale, the upper optimization problem is solved, and the optimal energy scheduling in the long-term can be achieved. At the fast scale, the energy balance between supply and demand of smart users can be realized in the short-term. Finally, simulation results illustrate the effectiveness of proposed method.

关键词： Smart user Microgrid energy management Multi-time scale time-hierarchal Model predictive control

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Development Tendency Study of Hybrid Electric Vehicle Transmission Considering an Optimized energy management Strategy

Development Tendency Study of Hybrid Electric Vehicle Transm...

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2018中国汽车工程学会年会

作者： SHI Tianze ZHAO Fuquan HAO Han LIU Zongwei Tsinghua Automotive Strategy Research Institute State Keylaboratory of Automotive Safety and EnergyTsinghua University

energy conservation and emission reduction have become increasingly significant for automobiles due to the severity of the current energy situation and Hybrid Electric Vehicle（HEV） technology is one of the most promising solutions.In this paper,the total efficiency of HEV powertrain is investigated.To improve the total efficiency,the engine should be regulated to work in high efficiency area,and drive the wheel directly.Based on this,a Direct Drive Area（DDA） energy management strategy is presented.Several typical HEV models are built to compare the fuel consumption using DDA and rule based strategies.Furthermore,the function of transmission system in HEV considering DDA is discussed.The transmission in HEV should regulate the engine to work in high efficiency area as much as possible,which is rather different with those in internal combustion engine vehicles.The functional change may lead transmission systems to have less gears with optimal ratios.If this conjecture is verified,the manufacturing cost of HEV could be largely reduced.

关键词： HEV transmission energy management engine

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A Homomorphic Cryptography Based Privacy-preserving Consensus Algorithm With Event-triggering in Distributed energy management

A Homomorphic Cryptography Based Privacy-preserving Consensu...

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第40届中国控制会议

作者： Qingze Zhuo Huifeng Zhang Xiaojing Hu Institute of Advanced Technology Nanjing University of Posts and Telecommunications

With consideration of privacy disclosure of consensus-based algorithm in distributed energy management（DEM）, this paper proposes a homomorphic cryptography based privacy-preserving consensus algorithm（HCPCA）. The optimal solution of HCPCA can maximize the social welfare while satisfying the constraints of load balance and upper/lower limits. In HCPCA, an encryption strategy is designed based on homomorphic encryption to preserve the privacy of electricity consumption information for consumers. Then, event-triggering strategy is used to reduce the heavy communication burden caused by information encryption. Finally, simulation results show the effectiveness of proposed algorithm.

关键词： Consensus energy management Privacy-preserving Homomorphic Cryptography Event-triggering

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Hybrid AC/DC Microgrid energy management Based on Renewable energy Sources Forecasting

Hybrid AC/DC Microgrid Energy Management Based on Renewable ...

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第36届中国控制会议

作者： Baolei Yuan Alian Chen Chunshui Du Chenghui Zhang School of Control Science and Engineering Shandong University

ISBN: (纸本)9781538629185

energy management is the core of economical and efficient operation for hybrid AC/DC microgrid. In this paper, renewable energy sources are forecast by using BP neural network based on modified particle swarm optimization（MPSO-BP）. Compared with traditional algorithm, the modified algorithm performs better in both search ability and speed. After forecasting, with the objectives of minimum total cost and minimum power loss, the optimal model is built. The output is optimized through coordinating all kinds of DGs. The simulation results verified the effectiveness of the proposed model in multi-objective optimization of hybrid microgrid. Through the energy management dispatch, the hybrid microgrid could realize the optimized operation level.

关键词： Hybrid AC/DC microgrid Renewable energy sources forecasting energy management

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Robust energy management Approach for a Microgrid Considering Uncertainties

Robust Energy Management Approach for a Microgrid Considerin...

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第40届中国控制会议

作者： Tengpeng Chen Yuhao Cao Xuebing Chen Yuhao Sun Shenzhen Research Institute of Xiamen University Department of Instrumental and Electrical Engineering Xiamen University Sungrow (Shanghai) Co. Ltd. National Centre for International Research on Photoelectric and energy Materials Yunnan University

Uncertainties of renewable energy sources and load demand have a significant effect on the microgrid operation. In this paper, a robust optimal energy management approach is proposed for a grid-connected microgrid where the adjustable uncertain sets are used to represent uncertainties. A novel statistic index is developed to evaluate the effectiveness of the robust optimization and obtain reasonable model parameters. Moreover, the optimal economic cost and the least environmental pollution are achieved simultaneously. Simulation results in different scenarios are given to verify the effectiveness of the robust optimization approach.

关键词： Microgrid energy management Uncertainty Robust optimization Environmental sustainability

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