Battery Management System Components Explained in Detail
16,Dec 2025
When I design a battery management system (BMS), I treat it as the “nervous system” of the pack. Every component has a clear job:
Measurement layer – cell voltage monitors, current sensors, and temperature sensing networks (NTCs, RTDs).
Control and computing layer – a dedicated BMS microcontroller unit (MCU) or battery controller that runs protection, SOC/SOH algorithms, and diagnostics.
Power and switching layer – power MOSFETs or contactors for charge/discharge control, pre-charge circuits, and cell balancing hardware.
Isolation and communication layer – galvanic isolation, CAN / LIN / UART / isoSPI transceivers for reliable communication with vehicle or system controllers.
Auxiliary power layer – DC‑DC converters and regulators that power the MCU, analog front-end (AFE), and sensors.
Together these BMS hardware components form a closed loop: sense → compute → act → communicate.
At architecture level, a battery management system is usually split into three logical blocks:
Cell monitoring units (CMUs)
Measure individual cell voltages and temperatures.
Implement local protection thresholds and cell balancing.
Pack controller
Aggregates data from CMUs.
Calculates state of charge (SOC), state of health (SOH), and power limits.
Interfaces with the vehicle control unit (VCU), inverter, or charger.
Power interface
High‑current path, including contactors or MOSFETs, pre‑charge, and current sensing.
This layered architecture scales from small e‑bike packs to high‑voltage EV battery systems and stationary energy storage.
I always separate what is wired from what is programmed:
BMS hardware layer
Battery monitoring ICs and AFEs
Shunt or Hall‑effect current sensors
NTC temperature sensing network
Power MOSFETs, drivers, DC‑DC converters
Isolation, fuses, and connectors
BMS software / firmware layer
Real‑time protection logic (OV, UV, OC, OT, short‑circuit)
SOC/SOH estimation and fuel‑gauge algorithms
Balancing strategy (when, how long, which cells)
Fault detection, logging, diagnostics, and communication protocols
Good BMS design tightly couples these layers: hardware provides clean, reliable data; software makes safe, fast decisions.
For different applications, I match the BMS layout to the pack size and voltage:
Centralized BMS architecture
One PCB manages all cells.
Simple and low‑cost; ideal for low‑voltage packs (e‑bikes, portable devices).
Wiring harness can become complex for larger packs.
Distributed BMS architecture
A small BMS board on each module or even on each cell.
Minimizes harness length and improves measurement accuracy.
Often used in high‑voltage EV packs and energy storage systems.
Modular BMS design
Repeated “BMS module” blocks (e.g., 12–16 cells each), daisy‑chained.
Balances cost, scalability, and serviceability.
Supports flexible pack configurations for different markets with the same core design.
Choosing between centralized, distributed, and modular BMS layouts is mainly about voltage level, cell count, service strategy, and cost targets.
A typical battery management system block diagram can be read from left to right along the energy and information paths:
Battery pack and cells
Series/parallel string of cells with sense lines for each cell tap.
Measurement front-end
Battery monitoring IC / AFE measuring cell voltages.
NTC temperature sensors on cells, busbars, and MOSFETs.
Current sense shunt or Hall‑effect sensor in the main negative or positive path.
Control core
BMS microcontroller or dedicated BMS controller running protection and SOC/SOH logic.
Memory for parameter sets and data logging.
Actuation and power path
Charge and discharge MOSFETs or contactors (often back‑to‑back MOSFETs).
Pre‑charge circuit, cell balancing network, and auxiliary power supply (DC‑DC).
Communication and isolation
CAN / CAN FD, LIN, UART, or isoSPI interfaces to the higher‑level system.
Isolation devices to maintain safety between high‑voltage and low‑voltage domains.
Reading the block diagram this way makes it easy to see how every BMS component contributes to measurement accuracy, safety, and reliable control of the battery pack.
A solid battery management system starts with reliable hardware. Below are the core BMS hardware components you actually rely on in day‑to‑day use, whether it’s an e‑bike pack, an energy storage rack, or an EV module.
The battery monitoring IC / analog front-end (AFE) is the “sensor hub” of the pack. It:
Measures each cell voltage with high accuracy
Reads temperature inputs from NTC sensors
Often includes built‑in ADCs, balancing drivers, and safety comparators
Modern AFEs support stacked / daisy‑chain communication (often via isoSPI or similar) so you can safely monitor high‑voltage packs with many series cells. In our own smart BMS designs, we use automotive‑grade AFEs similar to those discussed in this AI‑enabled smart BMS overview.
The BMS microcontroller unit runs all logic:
Collects data from the AFE and current sensors
Executes SOC / SOH algorithms and protection rules
Manages communication (CAN, UART, etc.)
Controls MOSFETs, relays, and balancing circuits
For higher-end systems (EV, industrial), we usually go for an automotive MCU or dedicated BMS controller with hardware safety features and enough performance to run model‑based algorithms.
Accurate cell voltage measurement circuits are critical for pack life:
Differential sensing per cell through the AFE
Proper filtering (RC filters) to reduce noise
Careful layout to handle high common‑mode voltages
Good measurement design is what lets you push usable capacity without hitting false overvoltage/undervoltage trips.
The NTC temperature sensing network protects your cells and helps optimize performance:
Multiple NTCs spread across the pack (cell middle, ends, hot spots near busbars)
Dedicated NTCs on power components (MOSFETs, shunt, DC‑DC)
Proper harness routing to avoid noise and connector issues
Smart thermal management in BMS means you get accurate pack temperature, not just “somewhere on the board.”
A BMS usually uses:
Current sense shunt
Low‑resistance metal resistor
High accuracy, low cost
Needs isolated or high-side current-sense amplifiers
Hall effect current sensor
Contactless, lower power dissipation
Great for high-current EV and storage systems
For critical applications, we often use redundant current sensing (e.g., shunt + Hall) for safety and fault checking.
Passive cell balancing uses small bleed resistors:
Excess charge is burned as heat
Simple, low-cost, robust
Best for small to medium packs, or where delta-SOC between cells is limited
Cell balancing ICs often integrate the bleed MOSFETs and timing control, simplifying layout.
Active cell balancing moves charge from high cells to low cells:
Switched‑capacitor balancing – capacitors shuttle charge between cells
Inductive / flyback balancing – transformers or inductors move energy across a wider cell range
Active balancing is attractive for EV and large ESS packs where energy recovered justifies the extra cost and complexity. Many modern production BMS use hybrid strategies (passive for fine trim, active for large imbalances).
BMS power MOSFETs handle pack connect/disconnect and sometimes pre‑charge:
Sized for pack voltage and peak/continuous current
Low Rds(on) to keep heat down
Often driven by a dedicated MOSFET pre-driver for fast, controlled switching
We treat the power stage as a safety component: derating, proper cooling, and strong gate drive design are a must.
High-side MOSFET switching: MOSFETs on the positive rail
Keeps pack negative at system ground
Preferred in automotive and industrial systems
Low-side MOSFET switching: MOSFETs on the negative rail
Simpler gate drive but can cause ground reference issues
Most modern professional BMS for vehicles and ESS use high-side switching for noise and safety reasons.
To block current both ways and prevent body-diode conduction, we use back‑to‑back MOSFETs:
Two MOSFETs in series, source-to-source
Allows independent control of charge and discharge paths
Enables strict overcurrent, short-circuit, reverse-polarity protection
This is standard in high-current BMS design.
For safe system integration, the BMS uses:
Galvanic isolation (digital isolators, isolated DC‑DCs) between pack and low-voltage logic
CAN communication in BMS – main bus for EV, ESS, and industrial systems
LIN communication in BMS – common in small automotive subsystems
UART interface in BMS – service port, configuration, local display
isoSPI / daisy‑chain interfaces – link multiple monitoring ICs in distributed BMS architectures
For large high-voltage packs, daisy-chain links are key to keeping wiring simple and EMI under control.
A dedicated battery fuel gauge IC or MCU algorithm handles:
SOC estimation (how full the battery is)
SOH estimation (capacity fade, resistance increase)
Remaining range / runtime calculations
Typical methods:
Coulomb counting (integrate current)
Open circuit voltage (OCV) method
Kalman filter SOC and model‑based estimation for accuracy over temperature, aging, and load
Advanced packs increasingly use AI‑enhanced algorithms, as covered in this breakdown of top AI algorithms in smart BMS systems.
The BMS needs its own clean power:
DC‑DC converter for MCU and gate drivers from pack voltage
Multiple rails (e.g., 12 V for drivers, 5 V / 3.3 V for logic and AFEs)
Low standby current for storage and idle modes
Stable auxiliary supply is crucial for accurate sensing and reliable safety actions.
Core battery safety electronics are built into hardware and firmware:
Overvoltage protection circuit – cell / pack voltage limits
Undervoltage protection circuit – prevents deep discharge
Overcurrent protection circuit – charge and discharge overcurrent
Short circuit protection in BMS – ultra-fast disconnect
Overtemperature protection in BMS – cells and power stage
These thresholds are tuned to the exact cell chemistry and application (DIY packs, e‑bikes, ESS, automotive), balancing protection, performance, and cycle life.
On the hardware side a BMS looks like sensors and MOSFETs. On the software side it’s basically a real‑time control system plus a battery analytics engine. I usually break it down into:
Low‑level drivers (ADC, CAN/LIN/UART, GPIO, timers)
Measurement and filtering (voltage, current, temperature)
Cell balancing control
Protection logic (OV/UV, OC, OT, short‑circuit)
State estimation (SOC, SOH, SOP)
Logging, diagnostics, and communication
Bootloader and update (OTA or service-port) if required
A solid BMS lives or dies on this software stack. The same hardware can feel “cheap” or “premium” depending purely on the firmware quality.
For small packs (e‑bikes, tools, LEVs), I often go bare‑metal:
Simple main loop + interrupts
Lowest cost, minimal flash/RAM, easy to certify
Good when you only have a few tasks (measurement, protection, comms)
For complex systems (EVs, energy storage, high‑voltage packs), I move to an RTOS:
Deterministic scheduling for SOC/SOH, comms, balancing, diagnostics
Easier to separate safety‑critical and non‑critical tasks
Cleaner scaling when you add telematics, cloud logging, or wireless BMS
If you’re targeting ISO 26262 or similar automotive‑grade design, an RTOS with safety support is usually the safer long‑term bet.
SOC estimation is where we turn raw sensor data into something the user actually cares about: “How much energy do I have left?”
Common building blocks:
Coulomb counting: integrates current over time
Open‑circuit voltage (OCV): uses cell voltage at rest vs a lookup table
Temperature compensation: SOC curves shift with temperature
Aging compensation: adjusts capacity and internal resistance over life
A good BMS fuses these methods instead of relying on just one.
Coulomb counting:
Pros: high short‑term accuracy, works under load
Cons: drifts over time due to current sensor offset and clock error
Use: main “live” SOC during charge/discharge
OCV method:
Pros: absolute reference when the pack is at rest and relaxed
Cons: slow; needs rest time, and curves depend on chemistry and temperature
Use: periodic recalibration of SOC drift
In production systems, I typically coulomb count continuously and correct with OCV when the pack is idle long enough.
For EVs and serious storage systems, we go further with Kalman filter or model‑based SOC/SOH:
Use an equivalent circuit model (e.g., Thevenin or R‑C network)
Fuse current, voltage, and temperature data with battery models
Provide better accuracy under dynamic loads and aging
Extended Kalman Filters (EKF) or Unscented Kalman Filters (UKF) are common for:
SOC (state of charge)
SOH (state of health: capacity, resistance)
SOP (state of power: how much power is safe right now)
This is where you really differentiate an automotive‑grade BMS from a basic protection board.
Protection limits are only half the story. I always design the firmware to:
Detect threshold violations: OV, UV, OC charge/discharge, OT/UT, short‑circuit
Classify fault severity: warning, recoverable fault, latched fault
Store freeze frames: timestamp, cell voltages, temps, pack current, status bits
Expose DTCs (diagnostic trouble codes) over CAN/LIN/UART to the host
Good diagnostics cut service time and reduce warranty risk, especially for fleets and shared mobility.
For global customers running fleets, rentals, or energy storage, data is everything. A robust BMS firmware typically logs:
Cycle count and cumulative amp‑hours / watt‑hours
Time spent at high SOC and high temperature (key aging drivers)
Daily min/max cell voltage and temperature
Peak current events and fault history
This data supports:
Warranty decisions and abuse detection
Predictive maintenance and remaining useful life estimates
Optimization of charging strategies and thermal management per region
On larger packs we often pair this with cloud‑connected gateways; on smaller systems we keep it local with downloadable logs.
If you’re serious about putting battery systems into EVs, motorcycles, ESS, or mobility devices, functional safety is not optional. A modern battery management system has to be designed from day one around standards like ISO 26262, IEC 62619, and UL 1973 – or you’ll get blocked at certification, or worse, face field failures and recalls.
For on-road vehicles, your BMS is treated as a safety-critical ECU:
Hazard analysis & risk assessment (HARA): Define what can go wrong (thermal runaway, loss of isolation, overcharge, etc.) and how severe it is for the driver, passengers, and people outside the vehicle.
Safety concept: Translate hazards into technical safety requirements for the BMS: safe shutdown, current limits, contactor control, thermal derating.
Safety mechanisms:
Redundant voltage and current sensing
Plausibility checks between sensors
Watchdogs on the BMS microcontroller
Safe states (open contactors, pack isolation, controlled discharge)
If you’re benchmarking real-world implementations, many automotive-grade and custom motorcycle BMS designs now highlight ISO 26262 capability as a key selling point, like the high-performance systems discussed in these custom BMS applications for electric motorcycles.
Depending on your use case and battery voltage/power, your BMS functions will be assigned ASIL (Automotive Safety Integrity Level) targets:
ASIL A–B: Common for light EVs, e‑bikes, and some LCVs
ASIL C–D: Common for high-voltage traction packs in passenger EVs
Typical safety goals:
Prevent cell overvoltage / undervoltage from reaching unsafe levels
Prevent overcurrent and short-circuit conditions from causing fire or damage
Prevent thermal runaway or uncontrolled overheating
Ensure the driver never loses propulsion or isolation warning without prior controlled behavior
We usually split these into ASIL-decomposed paths: one channel in hardware (fast protection) and one in software (supervision and diagnostics).
For stationary energy storage, telecom backup, forklifts, and industrial packs, functional safety leans more on product-level standards:
IEC 62619: Safety requirements for industrial lithium-ion batteries
Electrical abuse (overcharge, short, reverse)
Mechanical abuse (shock, vibration)
Thermal stability and fire behavior
UL 1973: Safety for stationary and motive auxiliary battery systems
Construction and spacing requirements
Protection electronics (BMS) behavior
Fault and abuse testing
Your BMS design directly affects whether the pack passes these tests. Cert labs care about:
How fast your overvoltage, undervoltage, overcurrent, and overtemperature protections react
Whether your BMS fails safe if power, firmware, or communication is lost
How your balancing and contactor logic behaves during faults
For higher ASIL or critical industrial applications, redundancy is what keeps things safe when a single component fails:
Redundant current sensing:
Two shunts, or shunt + Hall-effect sensor
Cross-checking readings and using the “safer” value if they disagree
Redundant voltage paths:
Primary cell monitoring IC chain + secondary “supervisory” monitor or pack-level check
Redundant temperature sensing:
Multiple NTCs per module; worst-case temperature is always used
Fail-safe contactor control:
Default-to-open logic if MCU, power, or gate driver fails
Hardware interlocks to prevent closing with unsafe voltage or isolation
The rule: any single failure must not lead directly to an unsafe battery state.
A safe BMS doesn’t just protect; it constantly proves that it’s still capable of protecting:
Self-diagnostics on power‑up and cyclically:
ADC checks, memory tests, watchdog supervision, communication timeouts
Sensor plausibility checks:
Compare pack voltage vs. sum of cell voltages
Compare temperature gradients across the pack
Compare current vs. change in SOC
Fault classification and handling:
Warnings (derate power, limit charge)
Severe faults (open contactors, lockout)
Traceable logging:
Store overcurrent events, high-temperature episodes, contactor cycles for warranty and field analysis
Many OEMs now view the BMS as the primary battery lifecycle tracking tool
If you’re targeting markets like e‑mobility or wheelchairs, pay attention to manufacturers who already embed strong diagnostics and safety paths into their designs, similar to what you’d see in an electric wheelchair BMS platform built for medical-grade reliability, such as our own wheelchair-focused BMS solutions.
In short: pick or design a BMS that treats ISO 26262, IEC 62619, and UL 1973 not as a checklist, but as the backbone of the architecture. That’s what separates hobby-grade boards from truly deployable, global-ready battery systems.
When I design a battery management system for lithium‑ion 18650 packs, I start from the use case: is it an e‑bike, portable power station, or small energy storage rack? That choice drives voltage range, peak current, safety level, and cost ceiling.
For a typical 10S–24S 18650 pack, a solid baseline looks like this:
Battery monitoring IC + AFE:
Multi‑cell monitor (e.g. 10–16 cells per IC) with built‑in ADC, cell balancing drivers, and isoSPI or daisy‑chain comms.
High accuracy (≤5 mV) to keep SOC and SOH estimation stable over time.
For high‑series packs, I’ll stack multiple AFEs in a daisy‑chain topology similar to a 24S BMS architecture used in EV and storage packs, like the ones broken down in this 24S BMS application example.
BMS microcontroller / controller:
Automotive‑grade MCU with CAN/CAN FD, enough RAM/Flash for SOC algorithms and logging.
Watchdog + hardware protection logic for fail‑safe shut‑down.
Current sensing:
Shunt resistor + differential amplifier up to ~150–200 A.
Hall‑effect sensor for isolation and less heat at higher currents or where galvanic isolation is a must.
Power MOSFET stage:
N‑channel back‑to‑back MOSFETs for charge and discharge, sized for at least 1.5× peak current.
Low Rds(on) to keep temperature rise and power loss under control.
If you’re working on 18650 mobile power or e‑bike packs, the selection logic is very close to what I use when choosing parts for an 18650 mobile power BMS, as outlined in this practical guide on how to choose a BMS for assembling mobile power with 18650 batteries.
On anything beyond low‑cost DIY, I move away from pure passive balancing:
Passive balancing (bleed resistors) is fine for small packs or tight budgets, but it wastes energy and creates extra heat.
Active cell balancing is worth it when:
Pack capacity is large (energy storage, high‑range e‑bike/EV).
Cycle life and fast charging are priorities.
In production, I often use:
Switched‑capacitor balancing for mid‑power systems; simpler, moderate efficiency.
Inductive / flyback topologies for high‑voltage, high‑energy packs, letting us move charge from high cells to low cells or even between modules.
We typically integrate balancing FETs and drivers inside the cell monitoring IC when possible, then scale up with external inductors or capacitors as needed.
For global customers, remote visibility and easy integration with existing systems are non‑negotiable:
CAN / CAN FD:
Default for EVs, e‑bikes, AGVs, and industrial storage.
Carries real‑time data: voltages, currents, temperatures, SOC, SOH, fault flags.
CAN FD gives higher throughput for more frequent logging and richer diagnostics.
Wireless BMS monitoring:
BLE or Sub‑GHz modules for local app access (service tools, fleet diagnostics).
In modular or rack storage, wireless links reduce harness cost and connector failures.
Encrypted links and gateway ECUs tie the BMS into cloud platforms for lifecycle tracking and warranty analytics.
The end goal is always the same: stable protection, accurate battery health tracking, and clean integration with your vehicle or energy system, without over‑engineering the hardware bill for your market and price point.
When I pick battery management system components, I start from the use-case, not the datasheet. Decide first: voltage, max continuous/peak current, chemistry (Li-ion, LFP, NMC), environment, and safety level required. Then:
Size your BMS power MOSFETs, shunts, and connectors from worst‑case current and ambient temperature.
Choose battery monitoring IC / AFE based on cell count, accuracy, and isolation needs (centralized vs modular vs distributed BMS).
Make sure the MCU or dedicated BMS controller has enough ADC channels, CAN/LIN/UART, and flash/RAM for your SOC/SOH algorithms and logging.
Check that all critical parts are automotive or industrial‑grade if you’re targeting harsh conditions.
For a feel of real-world integration, you can look at how a 24s 72 V smart BMS with CAN and RS485 is built and specified in this golf cart BMS example.
Match BMS architecture to pack size and complexity:
DIY / small packs (e-bike, scooter, powerwall)
Usually fine with a centralized BMS: one board, all cells wired in.
Lower cost, simpler wiring, easier debugging.
Industrial ESS, forklifts, telecom
Go modular BMS design: one cell monitoring board per module plus a master.
Easier to scale voltage and capacity, simpler field service.
Automotive EV, buses, high-voltage packs
Often distributed BMS architecture with daisy‑chain isoSPI or CAN between module boards.
Better EMC, isolation, and safety; easier to meet ISO 26262.
Different segments have very different BMS hardware and software expectations:
DIY / hobby / e-bike
Prioritize: low cost, simple wiring, basic protections, passive balancing.
Often UART/Bluetooth, basic SOC display, no ASIL requirements.
Industrial & commercial
Need: robust overcurrent/short‑circuit protection, event logging, CAN or RS485, good thermal monitoring.
Typically require standards like IEC 62619 / UL 1973 and long‑term reliability.
Automotive
Must support ISO 26262, defined ASIL levels, redundancy in sensing, advanced SOC/SOH algorithms, extensive diagnostics.
High‑reliability components, tested firmware architecture, and full lifecycle traceability.
If you’re sizing up a system for large arrays, the hardware–software tradeoffs in this article on BMS design for large battery packs are a good reality check.
I usually balance cost vs performance around these levers:
Monitoring IC choice
Higher‑end AFEs give better accuracy and faster sampling (improves SOC/SOH and safety), but cost more.
Balancing method
Passive cell balancing is cheap and simple, but wastes energy as heat.
Active balancing costs more and is more complex but pays off in large, high‑value packs (EV, ESS).
Communication
CAN / CAN FD and isoSPI add BOM and software complexity, but they’re worth it once you go beyond basic DIY.
Mechanical & connectors
Don’t cheap out here; failures usually start in wiring and connectors, not ICs.
Decide which failures you can’t accept (fire, downtime, warranty claims), then spend the budget to eliminate those first.
To future‑proof your BMS and avoid redesign every time the pack changes:
Use a modular BMS layout (module boards + master) so you can scale from 48 V to 400+ V by stacking modules.
Choose cell monitoring ICs that support daisy‑chain communication for higher cell counts.
Select an MCU family with headroom in CPU and memory for later SOC/SOH algorithm upgrades, more logs, and new comms like CAN FD or wireless BMS add‑ons.
Design the PCB and enclosure with spare connectors or footprints for adding extra sensors or comm channels later.
Think in product families, not one‑off designs. If your architecture can handle the “next size up” pack, you’re on the right track.
Battery management system components are evolving fast, driven by EVs, energy storage, and stricter safety rules. When I design or select a BMS now, I’m already thinking about where the tech will be in 3–5 years, not just what works today.
Wireless BMS cuts the long wiring harness between cell modules and the controller:
Less weight and volume – better range and easier pack assembly.
Simpler pack layout – no massive sensing harness, fewer connectors to fail.
Flexible module swapping – useful for large EV and ESS platforms.
Key points I care about:
Strong cybersecurity and encryption for cell data.
Redundant RF links and diagnostics to meet functional safety targets.
Automotive-grade wireless BMS is already in validation on premium EV platforms and will trickle down into cost‑sensitive packs like golf carts and e‑bikes soon.
We’re seeing the BMS, DC‑DC converter, and even traction inverter move closer together or into the same housing:
Shared cooling and power stages to cut cost and size.
Tighter control loops between battery, DC‑DC, and motor inverter.
Less wiring and fewer boxes, which matters a lot in high‑volume vehicles and compact ESS cabinets.
For smaller packs (e‑bike, golf cart, low‑voltage ESS), integrated solutions that combine BMS + DC‑DC + protection are already a strong value play. For example, a compact golf cart BMS with integrated control and communications can simplify the whole vehicle harness and reduce service time; that’s exactly the angle we focus on with our lithium golf cart BMS platforms.
SiC is not just for main inverters anymore. In BMS power paths and protection circuits, SiC MOSFETs give you:
Higher voltage margin for 800 V+ packs and future platforms.
Lower switching and conduction losses, enabling smaller heatsinks and busbars.
Better robustness at high temperature, which helps pack reliability in harsh climates.
I usually recommend SiC where:
Pack voltage is high (EV, bus, truck, industrial ESS).
Duty cycle and current are heavy enough that efficiency and thermal headroom pay back the higher silicon cost.
Cell monitoring ICs and analog front‑ends (AFEs) are becoming the real “brains” at module level:
More channels per IC, higher ADC resolution, and lower noise.
Integrated balancing FETs, diagnostics, and programmable safety thresholds.
Native support for isoSPI or daisy‑chain links, ideal for high‑voltage stacks.
Built‑in self‑test and redundancy features to help hit ISO 26262 goals.
For new designs, I look for AFEs that:
Support both wired and wireless topologies without redesigning the whole pack.
Have ASIL‑capable diagnostics and robust ESD/EMC performance.
Are backed by long‑term supply commitments, so the pack stays serviceable through its lifecycle.
If you’re working on smaller lithium packs right now, it’s often more cost‑effective to start from a standard BMS with integrated monitoring ICs and protection—for example, a compact 10S e‑bike BMS like our 36 V lithium BMS module—and then step up to next‑gen AFEs when you move into higher voltage or automotive‑grade projects.