Functional safety in BATTERY MANAGEMENT SYSTEMS
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1 Functional safety in BATTERY MANAGEMENT SYSTEMS
2 LiTHIUM BALANCE history st OEM cust. in production 300 projects completed ISO 9001 certified 400 projects completed 500 projects completed customers projects completed 2008 First commercial launch DONG investment 2006 Established
3 ISO where does it come from?
4 Automotive Safety Integrity Level (ASIL) Independent of the technologies implemented in the vehicle A B C D E 0 Incredibly unlikely E 1 Very low probability E 2 Low probability E 3 Medium probability E 4 High probability C 0 Controllable in general C 1 Simply controllable C 2 Normally controllable C 3 Difficult to control or uncontrollable S 0 No injuries S 1 Light to moderate injuries S 2 Severe to life-threatening (survival probable) injuries S 3 Life-threatening (survival uncertain) to fatal injuries
5 Determine the ASIL A B C D S1 S2 S3 C1 C2 C3 E1 QM QM QM E2 QM QM QM E3 QM QM ASIL A E4 QM ASIL A ASIL B E1 QM QM QM E2 QM QM ASIL A E3 QM ASIL A ASIL B E4 ASIL A ASIL B ASIL C E1 QM QM ASIL A E2 QM ASIL A ASIL B E3 ASIL A ASIL B ASIL C E4 ASIL B ASIL C ASIL D
6 Mapping of ASIL to SIL
7 The cost of implementation ISO26262 Company s effort and commitment: Strong Quality Assurance system Safety culture within the organization Implementation and utilization of a functional safety tool System documentation of the R&D work compliant to the standard Management commitment & support. Safety and redundant mechanisms required in the implementation of ISO could lead to an increased cost of the finished product. Some factors that might help to keep the cost down Utilization of Integrated Circuit to reduce components count and test Innovative use of decomposition rules to maximize the HW utilization Relocation of all non-safety functions to other sub-system Volume production of automotive components actually lower the price
8 ISO workflow Concept Phase Production Operation System Development System Verification Hardware Development Software Development Hardware Verification Software Verification
9 ESS boundary Diagram CHARGER INVERTOR MOUNTING Influence of neighboring systems HVIL VCU SERVICE TOOL BMS Dc/Dc CONTACTOR BOX BATTERY PACK THERMAL MANAGEMENT CHASSIS PROTECTION GROUND 24 VOLT POWER SUPPLY Customer Usage, Service personal Etc. Environment (temp, humidity, dust, Snow, water) Signal Interface HV interface / Power Supply Physical interface / Vibration EMC
10 ESS P-Diagram Request for Power Request for Charge Request for Discharge HV + HV- 12V power HVIL ok User Decision Software Bugs Defective Batteries Defective Electronics Faulty Wiring Vibration Water Ingress Dust Ingress High Temperature Low Temperature EMC Isolation Failure Noise Inputs Ignition Diagnostic Tool Thermal Management Current Monitor Enclosure Design Algorithm parameters Cell Balancing Data logging ESS Control Software Fuse Temperature monitoring Voltage monitor Mounting / installation Self Diagnostics Isolation monitoring Connect Driver Info Contactors Open or Close Delivering and accepting Power Cells maintained in Balance Error logs Warnings SOC indication Pre Charge Failure Inrush Current Welding of contactors Failure to open and close contactors Capacity loss leading to non recoverable battery pack Recoverable capacity loss Fire Explosion Melting of battery pack and other components Chemical Venting High Temperatures Incorrect Driver information Missing Driver information In correct self diagnostics Electrical Shock
11 Important parameters for safety Voltage Accuracy High speed update Reliable data The BMS performs thresholds sensing of Voltage, Current and Temperature AND make evaluation of the situation AND issue action e.g. controls chargers, loads and relays to assure safe operation FAST Current Precision Reliable data Sensing Evaluation Action Battery Management System Charger current Load current Relay On/Off Temperature Check point per cell Check point for other components (relays, contactor, DC/DC, wires...) Reliable data
12 Lithium Balance Safety Concept The safety concept is defined by five safety goals (SG) for the battery management system SG1: Prevent battery fires SG2: Non-battery fires SG3: Toxic fumes SG4: Maintain drivability SG5: Electrical shock The safety goals are split into functional safety requirements that can be managed by firmware or hardware
13 - High voltage battery pack + Schematic example for a BMS set up Contactor Master Control Unit voltage temperature open wire leakage Cell Monitoring Unit Cell voltage ASIL D Cell Temperature ASIL C PSU ASIL D Processor + RTOS ASIL D Current ASIL C Contactor control ASIL C Load Contactor Charger Contactor Current measurement
14 PSU and processor failure detection Master Control Unit Ignition Power SPI communication Processor PSU Error hardware signal Switchable power Aux If SPI communication is lost or the Processor signals an Error condition, the PSU will try to recover the Processor. If unsuccessful, it will enter a safe sate and wait for a new ignition signal.
15 How do we implement safety in our BMS CPU lock-step architecture, safe island approach. CRC validation of non-volatile memory. CRC validation of internal and external communication. MISRA-C compliant source code. Comprehensive static & dynamic validation of source code. Read/write ECC validation for internal memory. MCU Master Control Unit Dual Channel hall effect sensor inputs. Shunt sensor inputs. Precision check. Check for no drift. Open wire detection. Stuck at value check. Correct channel selection check. MUX decoder verification Dual Core Safety Master Controller ADC function verification ADC reference voltage verification MUX decoder verification Digital filter verification Open wire check Thermal shutdown protection Digital revision code verification Watchdog timer Balancing circuit verification CRC validation on communication. CMU Cell Monitoring Unit Precision check. Open wire detection. Check for no drift. Stuck at value check. Correct channel selection check. MUX decoder verification Proven combination of safety critical power supply and safety critical microcontroller. Protection against unstable supply and brownout. External windowed watchdog
16 Summary The n-bms is designed to have no undetected safety critical singlepoint failures. The detection methods include: Cell voltage input open wire detection Cell voltage and temperature measurement self test Internal and external MUX self test Power supply with watchdog protection, self test and CRC. Dual-core Lockstep cycle-by-cycle CPU CPU build in self test ECC on CPU FLASH and RAM CPU Clock and Voltage monitoring CMU Cell Monitoring Unit MCU Master Control Unit
17 Thank you Questions
18 BACK UP SLIDES
19 Hardware Implementation Balancing Methods Dissipative Balancing Nondissipative Balancing R R R R + simple, compact and cheap to implement + no waste in stand-by mode + relative low balancing current required - No efficiency when dissipation of wasted heat - Speed/current limited - Wasting energy is environmentally incorrect Cell-to-battery; battery-to-cell; cell-to-cell + Efficient in transferring energy + Potentially fast in balancing - More complex, larger volume, higher cost - Wasted stand-by power - Lower reliability due to complexity - High balancing current required
20 Balancing algorithms Voltage based SoC history based + Very simple method + No error in conversion to SoC + Accurate cell data for balancing at high SoC + Cell internal resistance is negligible - High current may be required for balancing - Higher current will result in higher heat + Lower balancing current could be used + Fewer cycles as balancing are done all the time. - High more PC power to compute SoC / slower - Requires larger memory to store the SoC - Possibility for inaccuracy when calculation of SoC 192 cells system balancing using voltage based algorithm
21 Battery Model The battery model is used to compensate from the ideal conditions to a real world scenario. The battery model will make the SOC estimation more precise outside the ideal operating range. It will also help application performance by dynamically adjusting system boundaries like allowed regen and discharge current.
22 Coulomb counting SOC estimation Coulomb counting SoC estimation: Accuracy depends on: - Sampling rate - Current measuring accuracy - Calibration points - Not well suited for Hybrid applications
23 Model based SoC estimation Model based SoC estimation: - Equivalent circuit model and the Electrochemical battery model - The Kalman filter is an algorithm for estimating unknown variables defined from noisy data input. - Normally in an SOC model based on input from syncroniced voltage, temperature and current sensors there are 200+ different unknown variables depending on model type. - Well suited for Hybrid applications without calibration points. The Model based SoC estimation is also very well suited for battery life optimization.
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