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Functional Safety and Secure CAN in Motor Control System Design for Electric Vehicles
Technical Paper
2017-01-1255
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Permanent magnet synchronous motors (PMSM) are widely used in the electric vehicles for their high power density and high energy efficiency. And the motor control system for electric vehicles is one of the most critical safety related systems in electric vehicles, because potential failures of this system can lead to serious harm to humans’ body, so normally a high automotive safety integrity level (ASIL) will be assigned to this system. In this paper, an ASIL-C motor control system based on a multicore microcontroller is presented. At the same time, due to the increasing number of connectivity on the vehicle, secure onboard communication conformed to the AUTOSAR standard is also implemented in the system to prevent external attacks.
In this paper, the functional safety development process of the motor control system is presented: in the item definition stage, the system is defined according to its functionalities and interaction with the environment and other items, and then the hazard analysis and risk assessment of the system is carried out to derive the safety goals and to assign the automotive safety integrity levels. For system architecture design, a proposed structure based on the E-GAS 3-layer monitor concept is proposed and functional safety requirements are assigned. The system is implemented with a multicore architecture microcontroller. For torque monitoring, a torque estimation algorithm for PMSMs is also presented. And considering the security threats to the vehicles, secure onboard communication usage is also described in the paper to provide a mechanism to authenticate and verify the CAN messages between the vehicle control unit and the motor control system.
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Citation
Wu, Z., lu, K., Zhu, Y., Lei, X. et al., "Functional Safety and Secure CAN in Motor Control System Design for Electric Vehicles," SAE Technical Paper 2017-01-1255, 2017, https://doi.org/10.4271/2017-01-1255.Data Sets - Support Documents
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References
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