Generic stochastic particle filter algorithm for predictive energy optimization of a Plug-in Hybrid Electric Vehicle extended by a battery temperature control and implemented on a Hardware-in-the-Loop system

2022 ◽  
Vol 120 ◽  
pp. 105002
Author(s):  
Franz Aubeck ◽  
Martin Lenz ◽  
Simon Mertes ◽  
Kevin Zylka ◽  
Stefan Pischinger
2004 ◽  
Author(s):  
Deepa Ramaswamy ◽  
Ryan McGee ◽  
Shiva Sivashankar ◽  
Amit Deshpande ◽  
Jace Allen ◽  
...  

Author(s):  
H Yeo ◽  
H Kim

A regenerative braking algorithm and a hydraulic module are proposed for a parallel hybrid electric vehicle (HEV) equipped with a continuous variable transmission (CVT). The regenerative algorithm is developed by considering the battery state of charge, vehicle velocity and motor capacity. The hydraulic module consists of a reducing valve and a power unit to supply the front wheel brake pressure according to the control algorithm. In addition, a stroke simulator is designed to provide a similar pedal operation feeling. In order to evaluate the performance of the regenerative braking algorithm and the hydraulic module, a hardware-in-the-loop simulation (HILS) is performed. In the HILS system, the brake system consists of four wheel brakes and the hydraulic module. Dynamic characteristics of the HEV are simulated using an HEV simulator. In the HEV simulator, each element of the HEV powertrain such as internal combustion engine, motor, battery and CVT is modelled using MATLAB SIMULINK. In the HILS, a driver operates the brake pedal with his or her foot while the vehicle speed is displayed on the monitor in real time. It is found from the HILS that the regenerative braking algorithm and the hydraulic module suggested in this paper provide a satisfactory braking performance in tracking the driving schedule and maintaining the battery state of charge.


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