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Design and Research of Intelligent Vehicle EPB Controller Based on ISO26262 Standard
Technical Paper
2019-01-5049
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
In recent years, the development of intelligent vehicle and new energy vehicles has advanced by leaps and bounds, which has further improved the safety requirements of controllers. And more and more component manufacturers are actively promoting the ISO 26262 standard “Road Vehicles-Functional Safety”. At the same time, the electronic parking brake (EPB) system is an indispensable electronic product of the intelligent vehicle, which brings convenience to drivers and improves vehicle safety. So it is necessary to develop an intelligent vehicle pneumatic EPB system based on the ISO 26262 standard to improve reliability and safety. In this paper, the concept phase of the ISO 26262 standard was analyzed and applied to the design of the EPB system. The risk assessment and risk analysis of the EPB system were carried out, and the corresponding safety objectives were formulated. In this paper, a dual MCU scheme was proposed to the EPB system, which contained the core MCU and the monitoring MCU. Then the hardware circuit is designed according to the proposed safety goal, including mutual reset circuit and arbitration circuit. And the three-layer software architecture of the EPB system was designed, including basic function layer, fault detection layer and monitoring layer. Finally, the functional verification experiment and the safety test were carried out. The experimental results show that the designed EPB controller not only meets the design requirements of the intelligent vehicle EPB system, the proposed control strategy can also detect faults accurately and respond in time. The EPB controller satisfies the proposed safety objectives and improves the reliability of the EPB system greatly.
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Song, M., Wang, H., Le Jia, T., and Wang, X., "Design and Research of Intelligent Vehicle EPB Controller Based on ISO26262 Standard," SAE Technical Paper 2019-01-5049, 2019, https://doi.org/10.4271/2019-01-5049.Data Sets - Support Documents
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