Real-time optimization power-split strategy for hybrid electric vehicles

This research focused on real-time optimization control to improve the fuel consumption of power-split hybrid electric vehicles. Particle swarm optimization (PSO) was implemented to reduce fuel consumption for real-time optimization control. The engine torque was design-variable to manage the energy distribution of dual energy sources. The AHS II power-split hybrid electric system was used as the powertrain system. The hybrid electric vehicle model was built using Matlab/Simulink. The simulation was performed according to US FTP-75 regulations. The PSO design objective was to minimize the equivalent fuel rate with the driving system still meeting the dynamic performance requirements. Through dynamic vehicle simulation and PSO, the required torque value for the whole drivetrain system and corresponding high-efficiency engine operating point can be found. With that, the two motor/generators (M/Gs) supplemented the rest required torques. The composite fuel economy of the PSO algorithm was 46.8 mpg, which is a 9.4% improvement over the base control model. The PSO control strategy could quickly converge and that feature makes PSO a good fit to be used in real-time control applications.

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An Optimized Real-Time Energy Management Strategy for the Power-Split Hybrid Electric Vehicles

IEEE Transactions on Control Systems Technology ◽

10.1109/tcst.2018.2796551 ◽

2019 ◽

Vol 27 (3) ◽

pp. 1194-1202 ◽

Cited By ~ 13

Author(s):

Jinglai Wu ◽

Jiageng Ruan ◽

Nong Zhang ◽

Paul D. Walker

Keyword(s):

Real Time ◽

Energy Management ◽

Electric Vehicles ◽

Management Strategy ◽

Hybrid Electric Vehicles ◽

Energy Management Strategy ◽

Power Split ◽

Hybrid Electric

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Real-Time Energy Management of Parallel Hybrid Electric Vehicles Using Linear Quadratic Regulation

Energies ◽

10.3390/en13215538 ◽

2020 ◽

Vol 13 (21) ◽

pp. 5538

Author(s):

Bảo-Huy Nguyễn ◽

João Pedro F. Trovão ◽

Ronan German ◽

Alain Bouscayrol

Keyword(s):

Real Time ◽

Energy Management ◽

Electric Vehicles ◽

Hybrid Electric Vehicles ◽

Engine Fuel ◽

Linear Quadratic ◽

Loop Control ◽

Parallel Hybrid ◽

Linear Quadratic Regulation ◽

Hybrid Electric

Optimization-based methods are of interest for developing energy management strategies due to their high performance for hybrid electric vehicles. However, these methods are often complicated and may require strong computational efforts, which can prevent them from real-world applications. This paper proposes a novel real-time optimization-based torque distribution strategy for a parallel hybrid truck. The strategy aims to minimize the engine fuel consumption while ensuring battery charge-sustaining by using linear quadratic regulation in a closed-loop control scheme. Furthermore, by reformulating the problem, the obtained strategy does not require the information of the engine efficiency map like the previous works in literature. The obtained strategy is simple, straightforward, and therefore easy to be implemented in real-time platforms. The proposed method is evaluated via simulation by comparison to dynamic programming as a benchmark. Furthermore, the real-time ability of the proposed strategy is experimentally validated by using power hardware-in-the-loop simulation.

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Towards Optimal Power Management of Hybrid Electric Vehicles in Real-Time: A Review on Methods, Challenges, and State-Of-The-Art Solutions

Energies ◽

10.3390/en11030476 ◽

2018 ◽

Vol 11 (3) ◽

pp. 476 ◽

Cited By ~ 22

Author(s):

◽

Keyword(s):

Real Time ◽

Power Management ◽

Electric Vehicles ◽

Hybrid Electric Vehicles ◽

State Of The Art ◽

Optimal Power ◽

Hybrid Electric

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Multirate Integration in Hybrid Electric Vehicle Virtual Proving Grounds

Volume 2: 24th Design Automation Conference ◽

10.1115/detc98/dac-5634 ◽

1998 ◽

Author(s):

Dario Solis ◽

Chris Schwarz

Keyword(s):

Real Time ◽

Electric Vehicle ◽

Time Scales ◽

Electric Vehicles ◽

Time Scale ◽

Hybrid Electric Vehicle ◽

Hybrid Electric Vehicles ◽

Differential Algebraic Equations ◽

Vehicle Systems ◽

Hybrid Electric

Abstract In recent years technology development for the design of electric and hybrid-electric vehicle systems has reached a peak, due to ever increasing restrictions on fuel economy and reduced vehicle emissions. An international race among car manufacturers to bring production hybrid-electric vehicles to market has generated a great deal of interest in the scientific community. The design of these systems requires development of new simulation and optimization tools. In this paper, a description of a real-time numerical environment for Virtual Proving Grounds studies for hybrid-electric vehicles is presented. Within this environment, vehicle models are developed using a recursive multibody dynamics formulation that results in a set of Differential-Algebraic Equations (DAE), and vehicle subsystem models are created using Ordinary Differential Equations (ODE). Based on engineering knowledge of vehicle systems, two time scales are identified. The first time scale, referred to as slow time scale, contains generalized coordinates describing the mechanical vehicle system that includs the chassis, steering rack, and suspension assemblies. The second time scale, referred to as fast time scale, contains the hybrid-electric powertrain components and vehicle tires. Multirate techniques to integrate the combined set of DAE and ODE in two time scales are used to obtain computational gains that will allow solution of the system’s governing equations for state derivatives, and efficient numerical integration in real time.

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