Approximate Dynamic Programming Real-Time Control Design for Plug-In Hybrid Electric Vehicles

2021 ◽  
Author(s):  
Wei Wang ◽  
Zhenjiang Cai ◽  
Shaofei Liu
Keyword(s):  
Dynamic Programming ◽  
Real Time ◽  
Electric Vehicles ◽  
Approximate Dynamic Programming ◽  
Hybrid Electric Vehicles ◽  
Control Design ◽  
Real Time Control ◽  
Time Control ◽  
Hybrid Electric

Computationally Efficient Optimal Power Management for Plug-In Hybrid Electric Vehicles With Spatial Domain Dynamic Programming

2008 ◽  
Author(s):  
Qiuming Gong ◽  
Yaoyu Li ◽  
Zhong-Ren Peng
Keyword(s):  
Dynamic Programming ◽  
Global Optimization ◽  
Real Time ◽  
Traffic Flow ◽  
Power Management ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Computationally Efficient ◽  
Hybrid Electric ◽  
Charge Depletion

The plug-in hybrid electric vehicles (PHEV), utilizing more battery power, has become a next-generation HEV with great promise of higher fuel economy. Global optimization charge-depletion power management would be desirable. This has so far been hampered due to the a priori nature of the trip information and the almost prohibitive computational cost of global optimization techniques such as dynamic programming (DP). Combined with the Intelligent Transportation Systems (ITS), our previous work developed a two-scale dynamic programming approach as a nearly globally optimized charge-depletion strategy for PHEV power management. Trip model is obtained via GPS, GIS, real-time and historical traffic flow data and advanced traffic flow modeling. The main drawback was the dependency of external server for obtaining the macroscale SOC profile, which makes it difficult to handle the impromptu change of driving decision. In this paper, a computationally efficient strategy is proposed based on road segmentation and lookup table methods. Simulation results have shown its great potential for real-time implementation.

Optimal control of fuel economy in parallel hybrid electric vehicles

2007 ◽  
Vol 221 (9) ◽  
pp. 1097-1106 ◽  
Author(s):  
J Pu ◽  
C Yin
Keyword(s):  
Optimal Control ◽  
Real Time ◽  
Electric Vehicles ◽  
Fuel Economy ◽  
Hybrid Electric Vehicles ◽  
Real Time Control ◽  
Simulation Code ◽  
Computation Efficiency ◽  
Parallel Hybrid ◽  
Hybrid Electric

A mathematical model of optimal control of fuel economy for parallel hybrid electric vehicles (HEVs) and its dynamic programming (DP) recursive equation and numerical DP algorithm are presented. The effect of frequent gear shifting and engine stop-starting on drivability and fuel economy are both taken into account in the cost function. To overcome the curse of dimensionality of numerical DP, an algorithm restricting the exploring region is proposed to reduce largely the computational complexity, and the quantization increments are carefully selected to balance computation accuracy and efficiency. Furthermore, instead of being simplified, the system model is converted into a real-time simulation code by using MATLAB/RTW to improve the computation efficiency. Finally, a case study is presented. The vehicle testing results, the simulation results, and the DP results are compared and analysed, indicating that the maximum performance and the optimal control policy of the HEV can be determined by the algorithm proposed in this paper within an acceptable time and that the results can be used to evaluate and improve the real-time control strategy.

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

Energies ◽  
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.

Optimal control of a novel uninterrupted multi-speed transmission for hybrid electric mining trucks

2019 ◽  
Vol 233 (12) ◽  
pp. 3235-3245 ◽  
Author(s):  
Weiwei Yang ◽  
Jiejunyi Liang ◽  
Jue Yang ◽  
Nong Zhang
Keyword(s):  
Dynamic Programming ◽  
Real Time ◽  
Control Strategy ◽  
Dynamic Models ◽  
Fuel Efficiency ◽  
Real Time Control ◽  
Traction Motor ◽  
Time Control ◽  
Power Split ◽  
Shift Strategy

Considering the energy consumption and specific performance requirements of mining trucks, a novel uninterrupted multi-speed transmission is proposed in this paper, which is composed of a power-split device, and a three-speed lay-shaft transmission with a traction motor. The power-split device is adapted to enhance the efficiency of the engine by adjusting the gear ratio continuously. The three-speed lay-shaft transmission is designed based on the efficiency map of traction motor to guarantee the drivability. The combination of the power-split device and three-speed lay-shaft transmission can realize uninterrupted gear shifting with the proposed shift strategy, which benefits from the proposed adjunct function by adequately compensating the torque hole. The detailed dynamic models of the system are built to verify the effectiveness of the proposed shift strategy. To evaluate the maximum fuel efficiency that the proposed uninterrupted multi-speed transmission could achieve, dynamic programming is implemented as the baseline. Due to the “dimension curse” of dynamic programming, a real-time control strategy is designed, which can significantly improve the computing efficiency. The simulation results demonstrate that the proposed uninterrupted multi-speed transmission with dynamic programming and real-time control strategy can improve fuel efficiency by 11.63% and 8.51% compared with conventional automated manual transmission system, respectively.

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