A Flexible Hardware-in-the-Loop Testing System for Hybrid Powertrain

Author(s):  
Shugang Jiang ◽  
Dharshan Medonza ◽  
James Kitchen
2012 ◽  
Vol 490-495 ◽  
pp. 13-18 ◽  
Author(s):  
Ran Chen ◽  
Lin Mi ◽  
Wei Tan

Hardware-in-the-loop simulation (HILS) is a scheme that incorporates some hardware components of primary concern in the numerical simulation environment. This paper discusses the implementation and benefits of using the HIL testing system for electronic control unit of dual-clutch transmission (DCT) vehicle.


2012 ◽  
Vol 466-467 ◽  
pp. 1084-1088
Author(s):  
Yuan Liu ◽  
Zhi Xue Wang ◽  
Ru Ke Zhuang ◽  
Jian Hui Ma

In order to meet the development and test demands of the body control module, the simulation testing system of the automobile Body Control Module was designed with the Hardware-in-the-loop simulation technology. Based on the function of BCM, the key technology of modeling and simulation, interface design and automation testing were explained to implement real-time simulation and testing for BCM. It assure the development quality, shorten the design period and reduce the product cost.


Author(s):  
Sara Mohon ◽  
Satadru Dey ◽  
Beshah Ayalew ◽  
Pierluigi Pisu

Hardware-in-the-loop (HIL) platforms enable rapid evaluation of different system configurations and energy management strategies for electrified/hybrid powertrains without building full vehicle prototypes. This paper outlines a HIL platform for a series hybrid powertrain and discusses particular control strategies. The main hardware components of the platform are a gasoline generator, a lead acid battery pack, a bi-directional dc/dc converter, a programmable dc load, strain gauges, and a rotary encoder. Along with these hardware components, a real-time control prototyping system is used to implement energy management strategies and monitor several signals form the HIL platform. The effectiveness and performance of this platform is demonstrated by implementing two versions of the Equivalent Consumption Minimization Strategy (ECMS). The first version uses a constant equivalence factor for weighting the cost of electrical energy storage, while the second version uses an adaptive equivalence factor based on the deviation of battery state of charge (SOC) from a reference SOC.


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