scholarly journals Optimization of rule-based energy management strategies for hybrid vehicles using dynamic programming

2021 ◽  
Vol 184 (1) ◽  
pp. 3-10
Author(s):  
Di Zhu ◽  
Ewan Pritchard ◽  
Sumanth Dadam ◽  
Vivek Kumar ◽  
Yang Xu
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Measurement System ◽  
Hybrid Electric Vehicle ◽  
Management Strategies ◽  
Optimization Approach ◽  
Rule Based ◽  
Management Optimization ◽  
Vehicle Test ◽  
Vehicle Dynamic Model

Reducing energy consumption is a key focus for hybrid electric vehicle (HEV) development. The popular vehicle dynamic model used in many energy management optimization studies does not capture the vehicle dynamics that the in-vehicle measurement system does. However, feedback from the measurement system is what the vehicle controller actually uses to manage energy consumption. Therefore, the optimization solely using the model does not represent what the vehicle controller sees in the vehicle. This paper reports the utility factor-weighted energy consumption using a rule-based strategy under a real-world representative drive cycle. In addition, the vehicle test data was used to perform the optimization approach. By comparing results from both rule-based and optimization-based strategies, the areas for further improving rule-based strategy are discussed. Furthermore, recent development of OBD raises a concern about the increase of energy consumption. This paper investigates the energy consumption increase with extensive OBD usage.

Analysis and Control of Torque Split in Hybrid Electric Vehicles by Incorporating Powertrain Dynamics

2018 ◽  
Vol 140 (11) ◽  
Author(s):  
Mehran Bidarvatan ◽  
Mahdi Shahbakhti
Keyword(s):  
Steady State ◽  
Energy Consumption ◽  
Energy Management ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Internal Combustion Engines ◽  
Dynamic Models ◽  
Management Control ◽  
Drive Cycle ◽  
Hybrid Electric

Hybrid electric vehicle (HEV) energy management strategies usually ignore the effects from dynamics of internal combustion engines (ICEs). They usually rely on steady-state maps to determine the required ICE torque and energy conversion efficiency. It is important to investigate how ignoring these dynamics influences energy consumption in HEVs. This shortcoming is addressed in this paper by studying effects of engine and clutch dynamics on a parallel HEV control strategy for torque split. To this end, a detailed HEV model including clutch and ICE dynamic models is utilized in this study. Transient and steady-state experiments are used to verify the fidelity of the dynamic ICE model. The HEV model is used as a testbed to implement the torque split control strategy. Based on the simulation results, the ICE and clutch dynamics in the HEV can degrade the control strategy performance during the vehicle transient periods of operation by around 8% in urban dynamometer driving schedule (UDDS) drive cycle. Conventional torque split control strategies in HEVs often overlook this fuel penalty. A new model predictive torque split control strategy is designed that incorporates effects of the studied powertrain dynamics. Results show that the new energy management control strategy can improve the HEV total energy consumption by more than 4% for UDDS drive cycle.

scholarly journals Energy management strategies for combined heat and electric power micro-grid

2016 ◽  
Vol 20 (4) ◽  
pp. 1091-1103 ◽  
Author(s):  
Marina Barbaric ◽  
Drazen Loncar
Keyword(s):  
Energy Management ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Optimization Technique ◽  
Management Strategies ◽  
Distribution Networks ◽  
Energy Storage System ◽  
Optimization Approach ◽  
Micro Grid ◽  
Additional Rule

The increasing energy production from variable renewable energy sources such as wind and solar has resulted in several challenges related to the system reliability and efficiency. In order to ensure the supply-demand balance under the conditions of higher variability the micro-grid concept of active distribution networks arising as a promising one. However, to achieve all the potential benefits that micro-gird concept offer, it is important to determine optimal operating strategies for micro-grids. The present paper compares three energy management strategies, aimed at ensuring economical micro-grid operation, to find a compromise between the complexity of strategy and its efficiency. The first strategy combines optimization technique and an additional rule while the second strategy is based on the pure optimization approach. The third strategy uses model based predictive control scheme to take into account uncertainties in renewable generation and energy consumption. In order to compare the strategies with respect to cost effectiveness, a residential micro-grid comprising photovoltaic modules, thermal energy storage system, thermal loads, electrical loads as well as combined heat and power plant, is considered.

Rule-based energy management strategies for hybrid vehicles

2007 ◽  
Vol 1 (1) ◽  
pp. 71 ◽  
Author(s):  
Theo Hofman ◽  
Maarten Steinbuch ◽  
Roell Van Druten ◽  
Alex Serrarens
Keyword(s):  
Energy Management ◽  
Management Strategies ◽  
Hybrid Vehicles ◽  
Rule Based

Development of Energy Management Strategies for Heavy Mobile Machinery

2013 ◽  
Author(s):  
Antti Lajunen
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Underground Mining ◽  
Management Strategies ◽  
Operating Efficiency ◽  
Optimal Power ◽  
Power Split ◽  
Electric Loader ◽  
Mobile Machinery ◽  
Task Oriented

This paper introduces a method for developing energy management strategies (EMS) for task-oriented heavy mobile machinery. The case application is a hybrid underground mining loader but the method is also used for a diesel-electric and electric loader. Depending on the optimization target, the sequence for optimal power-split between the engine-generator (gen-set) and battery is defined. The minimization of the energy consumption and maximization of the operating efficiency are used as the optimization targets. The developed method is based on dynamic programming simulations which generate the optimal power-split for the evaluation of the control parameters. The simulation results showed that there are no significant differences between the two optimization targets in terms of the control sequence of the hybrid loader. The major difference was observed in the battery charging power which was much lower in the case of the minimization of the energy consumption.

scholarly journals Adaptive Rule-Based Energy Management Strategy for a Parallel HEV

Energies ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 4472 ◽  
Author(s):  
Rishikesh Mahesh Bagwe ◽  
Andy Byerly ◽  
Euzeli Cipriano dos Santos ◽  
Ben-Miled
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Duty Cycle ◽  
Management Strategy ◽  
Hybrid Electric Vehicle ◽  
Detailed Knowledge ◽  
Energy Management Strategy ◽  
Rule Based ◽  
Engine Efficiency ◽  
Efficiency Map

This paper proposes an Adaptive Rule-Based Energy Management Strategy (ARBS EMS) for a parallel hybrid electric vehicle (HEV). The aim of the strategy is to facilitate the aftermarket hybridization of medium- and heavy-duty vehicles. ARBS can be deployed online to optimize fuel consumption without any detailed knowledge of the engine efficiency map of the vehicle or the entire duty cycle. The proposed strategy improves upon the established Preliminary Rule-Based Strategy (PRBS), which has been adopted in commercial vehicles, by dynamically adjusting the regions of operations of the engine and the motor. It prevents the engine from operating in highly inefficient regions while reducing the total equivalent fuel consumption of the vehicle. Using an HEV model developed in Simulink®, both the proposed ARBS and the established PRBS strategies are compared over an extended duty cycle consisting of both urban and highway segments. The results show that ARBS can achieve high MPGe with different thresholds for the boundary between the motor region and the engine region. In contrast, PRBS can achieve high MPGe only if this boundary is carefully established from the engine efficiency map. This difference between the two strategies makes the ARBS particularly suitable for aftermarket hybridization where full knowledge of the engine efficiency map may not be available.

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