Data Management for Automotive ECUs Based on Hybrid RAM-NVM Main Memory

More and more Electronic Control Units (ECUs) are applied into the automotive electrical and electronic systems. The system data and user data which ECUs need should be stored in Non-Volatile Memory (NVM) in order to avoid losing these data. However, NVM has the limitation on the numbers of writing so that the NVM is not suitable for the main memory [1]. In this paper, we propose a vehicle data allocation (VDA) algorithm that can reduce the writing times of NVM (if NVM is used to be main memory) or save random access memory (RAM) space (if RAM is used to be main memory) in automotive electronic control systems. In our method, both RAM and NVM are used as main memory. The data from automobile is classified into three categories and the automobile running phase is also divided into three phases. Our algorithm targets to manage the different categories data in NVM and RAM in different phases through the characteristics of the data. Our proposed algorithm can reduce the writing times in NVM effectively. Comparing with using NVM as the main memory, our method will reduce several hundred thousand writing times in NVM. Based on results of the case study, our algorithm can reduce on average 25% RAM space in the start phase, and even reduce on average 62.5% in most runtime.

[1]  Edwin Hsing-Mean Sha,et al.  Curling-PCM: Application-specific wear leveling for phase change memory based embedded systems , 2013, 2013 18th Asia and South Pacific Design Automation Conference (ASP-DAC).

[2]  Jeongho Son,et al.  A Non-Volatile Memory Management Scheme for Automotive Electronic Control Units , 2012, 2012 International Conference on Connected Vehicles and Expo (ICCVE).

[3]  Zhiping Jia,et al.  Unified DRAM and NVM hybrid buffer cache architecture for reducing journaling overhead , 2016, 2016 Design, Automation & Test in Europe Conference & Exhibition (DATE).

[4]  Min Wu,et al.  Design and application of testing system for pneumatic ABS ECU , 2014, Proceeding of the 11th World Congress on Intelligent Control and Automation.

[5]  Shuichi Oikawa,et al.  Preliminary Analysis of a Write Reduction Method for Non-volatile Main Memory on Jikes RVM , 2013, 2013 First International Symposium on Computing and Networking.

[6]  Zhu Wang,et al.  Endurance-Aware Allocation of Data Variables on NVM-Based Scratchpad Memory in Real-Time Embedded Systems , 2015, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[7]  Shuichi Oikawa,et al.  An architecture of operating system utilizing non-volatile main memory and heterogeneous multi-core , 2013, 2013 IEEE/ACIS 12th International Conference on Computer and Information Science (ICIS).

[8]  Ki-Ho Lee,et al.  Implementation of approach to functional safety compliant brushless DC motor control system , 2014, 2014 14th International Conference on Control, Automation and Systems (ICCAS 2014).

[9]  Kartik Mohanram,et al.  CompEx: Compression-expansion coding for energy, latency, and lifetime improvements in MLC/TLC NVM , 2016, HPCA.