LUMO SOLAR POWER

LUMO Cloud Monitoring Platform

Product Overview and Interface Guide

Cover image – live device overview with pack voltage, SOC, SOH, cell and temperature summaries.

LIVE VISIBILITY Pack, cell and sensor data in one connected view

EVENT TRACEABILITY Alarm history, duration and recovery status

REMOTE SERVICE Historical analysis before unnecessary site visits

Interface examples based on LUMO platform data | Demonstration period: May-August 2026

Executive Summary

CORE POSITIONING  The LUMO Cloud Monitoring Platform brings cell-level data, system status, historical trends and alarm records into one remote service interface. Installers and service teams can see the issue, understand the operating sequence and retain evidence before arriving on site.

• Real-time visibility:View pack voltage, current, SOC, SOH, individual cell voltage, temperature, relay status and communication state.
• Cell-level diagnostics:Quickly identify the highest and lowest cell voltages, voltage spread, temperature extremes and corresponding channels.
• Historical traceability:Replay cell, pack, current and temperature curves by time to establish an operating and fault-evidence trail.
• Closed-loop alarm records:Retain alarm name, level, start time, duration, end time and recovery status.
• Remote service foundation:Platform data supports parameter checks, anomaly localization, Level 4 protection-event analysis and remote balancing decisions.

Platform capabilities at a glance

Evidence area	Visible example	Operational meaning
Live device snapshot	268.3 V pack; 100% SOC; 96.7% SOH	A compact health and operating-state summary
Cell coverage	80 online cell-voltage channels	Cell-by-cell consistency and outlier visibility
Temperature coverage	20 online thermistors	Thermal distribution and sensor-level diagnosis
Snapshot cell spread	3.409 V max / 3.336 V min (73 mV)	An actionable consistency indicator at that moment
Historical diagnostics	Alarm, operating-hours and event-replay views	Evidence for remote service and root-cause review

Note: The values shown are operating examples from the displayed devices and time windows. Actual readings vary by system configuration and operating conditions.

One connected path from the cells to the service team

The platform converts raw BMS telemetry into a service workflow. Data moves from cell and temperature sensors through the battery-management and high-voltage control layers, then to the LUMO cloud for live dashboards, alarm records and historical analysis.

DATA FLOW  Cells & sensors  →  Udan BMS  →  LMCB300 high-voltage control  →  network / Wi-Fi  →  LUMO cloud  →  installer and service team

Platform information layers

Layer	Typical data	Primary use
Device identity	HWID, serial number, battery number, model, site/city	Asset identification and fleet organization
System state	Wake-up signal, charge/discharge state, relay status, connection state	Confirm whether the system is awake and how it is operating
Pack health	Pack voltage, current, SOC, SOH, average voltage and temperature	Fast condition assessment
Cell detail	Individual cell voltage, maximum/minimum cell, voltage difference	Detect drift and capacity-limiting outliers
Thermal detail	Individual thermistor values, maximum/minimum temperature	Identify hotspots, cold sensors or channel faults
Protection evidence	Alarm name, level, duration, end time and repair state	Trace events and support warranty/service diagnosis
Historical analytics	Operating hours, voltage, temperature and current trends	Understand actual usage and replay abnormal events

Customer value

• Commission with clearer evidence: confirm communications, online channels and operating state from one screen.
• Diagnose before travelling: compare live values, event history and historical curves remotely.
• Protect battery health: identify cell-voltage spread, abnormal temperature and repeated protection events earlier.
• Support accountability: retain a time-stamped operating record when settings or usage patterns are questioned.

The live dashboard turns a complex battery into one readable status view

The device overview combines identity, connection status, pack values, cell extremes and temperature extremes. It is the first screen a remote service technician can use to decide whether the issue is electrical, thermal, communications-related or configuration-related.

Figure 1. Live device overview – snapshot at 5 August 2026, 15:48:11.

Visible metric	Example value	How to read it
System status	Discharge	The controller reports the system in discharge state; instantaneous current is 0 A at this exact sample.
Pack voltage	268.3 V	Total battery-string voltage at the snapshot time.
SOC / SOH	100% / 96.7%	Estimated charge level and state of health reported by the BMS.
Average cell / temperature	3.36 V / 19.80°C	Compact indicators of electrical and thermal operating condition.
Online channels	80 cell voltages / 20 thermistors	Only confirmed online channels should be used for diagnostics.
Cell extremes	3.409 V (#7) / 3.336 V (#80)	The 73 mV spread identifies the cells that set the instantaneous range.
Temperature extremes	21°C (#1) / 18°C (#17)	A narrow 3°C active-sensor range in this snapshot.

High-frequency records preserve the system state, not just the latest number

The telemetry table records sequential device samples with time stamps. In the visible window, samples arrive roughly every 31-33 seconds, allowing service teams to distinguish a transient event from a stable condition.

Figure 2. Time-stamped system telemetry – 17 visible records from 15:31:47 to 15:40:46 on 5 August 2026.

Visible pattern

• WAKEUP1 and Discharge remain constant throughout the visible sample window.
• SOC remains 100%, SOH 96.7% and pack voltage 268.30 V across the shown records.
• Control power is approximately 23.500-23.531 V when the millivolt field is converted to volts.
• HV1 follows total battery voltage at 268.3 V, while unused or unavailable HV channels display zero.

INTERPRETATION RULE  Values marked “invalid” are unavailable measurements, not zero insulation resistance. They must be excluded from health calculations and customer-facing claims.

Maximum and minimum values reveal which cell or sensor is limiting the pack

The max/min telemetry view is designed for fast outlier detection. Instead of scanning every cell manually, the platform identifies the highest and lowest cell, their channel numbers, the voltage difference and the hottest/coldest active sensors.

Figure 3. Maximum/minimum cell and temperature telemetry – visible interval around 15:30-15:39 on 5 August 2026.

Observed field	Visible range	Service implication
Maximum cell voltage	3.410 V	The highest cell is stable, while the channel identity changes among several near-equal cells.
Minimum cell voltage	3.335-3.336 V	Cell #80 is repeatedly identified as the minimum in the shown interval.
Cell-voltage difference	0.074-0.075 V	The instantaneous spread is 74-75 mV and should be interpreted against SOC, current and operating state.
Maximum / minimum temperature	21°C / 18°C	The active sensors show a narrow 3°C range.
HV5 value	6553.5	Likely an invalid/uninitialized channel value; it is not physically credible as a measured battery voltage.

Cell-by-cell history makes voltage drift visible over time

The detailed cell table shows each cell voltage at every recorded time. The interface example displays the first 17 cell columns; the device overview confirms that 80 cell-voltage channels are online, so the table continues beyond the visible crop.

Figure 4. Individual cell-voltage history – visible channels #1 to #17.

What the visible cells show

• Most visible channels remain around 3,408-3,410 mV during the displayed interval.
• Cell #6 remains near 3,352 mV, cell #14 near 3,351-3,352 mV and cell #17 near 3,341 mV.
• The table supports persistence checks: a repeatedly low channel is more diagnostically useful than a single isolated sample.

IMPORTANT  The complete 80-cell dataset is required before ranking the lowest cells. In the live summary, cell #80 is the overall minimum at 3.336 V, even though it is outside this cropped view.

Distribution charts separate active sensors from unused channels

The cell distribution page gives a quick visual map of all configured measurement channels. Active cell voltages cluster near 3.4 V and active temperatures near 18-21°C. The sharp step to zero voltage after channel #80 and to -41°C after thermistor #20 indicates unused or unavailable channels in this interface configuration.

Figure 5. Cell-voltage and temperature distribution across configured channels.

DATA HYGIENE  Zero-voltage and -41°C placeholder values must be filtered by online-channel status. They should not be included in minimum, average, alarm or fleet-health calculations.

Why this view matters

• It makes isolated low cells or hot sensors visually obvious.
• It confirms how many channels are actively reporting before deeper analysis begins.
• It helps distinguish a real battery condition from an unconfigured input or sensor-mapping problem.

Alarm history converts protection events into a service record

The alarm table preserves what happened, when it started, how severe it was, how long it lasted and how it ended. This is essential for remote diagnosis, warranty discussions and validation of inverter or charging settings.

Figure 6. Alarm history – 23 visible ChgOV records from 20 July to 5 August 2026.

Alarm-history capabilities

• All 23 visible records are labelled ChgOV (charging over-voltage), Battery Alarm and Level 1.
• Visible durations range from 9 minutes to 5 days.
• The displayed records end in “Alarm repair”, indicating that the listed events are historical or recovered rather than active alarms at the displayed time.
• Repeated events justify checking charge-voltage limits, inverter settings, cell spread and the alarm threshold configuration.

SERVICE VALUE  A time-stamped event record cannot determine responsibility by itself, but it gives technicians the evidence needed to separate product faults from incorrect settings, abnormal use or communications problems.

Statistical analysis shows how the battery is actually being used

Operating-hour analysis summarizes daily charge and discharge behaviour across a selected period. The visible chart is filtered from 7 May to 4 August 2026, with the plotted series beginning around 20 May.

Figure 7. Daily operating hours – charge and discharge duration across the selected May-August 2026 period.

How to read the trend

• Discharge duration is generally high, mostly around 20-24 hours per day in the visible period.
• Charge duration is usually shorter, with several visible spikes that warrant correlation with operating schedules and alarm history.
• A pronounced late-July drop in discharge hours and simultaneous rise in charge hours provides a clear investigation point.

Values above are approximate visual readings from the chart. Exported raw data is required for exact totals, averages and performance comparisons.

Historical charting links cell spread, pack voltage, temperature and current

The historical chart aligns four data families on the same time window: maximum/minimum cell voltage, pack voltage, maximum/minimum temperature and current/SOC. This makes it possible to see whether voltage divergence occurs during a current event, whether temperature changes at the same time and whether the pack recovers afterwards.

Figure 8. Historical event replay – 5 August 2026, 00:00 to approximately 15:49.

Visible event pattern

• Three pronounced negative-current excursions coincide with sharp pack-voltage dips and temporary changes in maximum/minimum cell voltage.
• A later positive-current peak coincides with a pack-voltage rise; current sign convention should be confirmed before labelling the direction as charge or discharge.
• Active temperature traces remain within an approximate 15-22°C range in the displayed window.
• The chart supports event correlation, but exact current, energy and duration calculations require the downloadable time-series data.

The platform supports a complete remote-service workflow

1. Find the device.Confirm HWID, serial number, model, location, connection and latest device time.
2. Check live health.Review pack voltage/current, SOC, SOH, average voltage and temperature.
3. Check consistency.Identify maximum/minimum cell, voltage difference and temperature extremes.
4. Review alarms.Confirm the event name, level, duration, recovery state and recurrence pattern.
5. Replay history.Align current events with pack voltage, cell spread, SOC and temperature.
6. Take action.Review settings, support remote balancing, monitor recovery or dispatch a technician with a defined task.

Connection to LUMO Level 4 Protection

The cloud platform is the evidence and service layer around LUMO’s protection architecture. When extreme depletion or another critical condition causes the LMCB300 smart breaker to trip, the platform can preserve the preceding SOC, voltage, current, alarm and operating-history context. This helps the service team understand why the physical protection acted and what should be checked before restart.

Connection to adaptive remote balancing

Real-time cell visibility and stored charging curves provide the data foundation for Udan’s remote balancing workflow. After a completed charge lasting more than 15 minutes, the platform can analyse the full charging curve, estimate cell-capacity difference through curve fitting and calculate a personalized balance time. This is data-driven remote balancing, not a claim that balancing is continuously active every second.

Confirmed platform strengths

Capability	Customer benefit	Interface reference
Live cell-to-pack visibility	Faster status checks and earlier drift detection	Figures 1-5
Time-stamped telemetry	Distinguishes persistent conditions from transients	Figures 2-4
Alarm lifecycle records	Improves fault review and service traceability	Figure 6
Usage statistics	Shows how the system operates over weeks and months	Figure 7
Multi-signal event replay	Correlates current, voltage, temperature and cell spread	Figure 8

Data dictionary and interpretation rules

Field	Plain-English meaning	Interpretation note
SOC	Estimated state of charge	Use with current and voltage; 100% does not mean every cell is identical.
SOH	Estimated state of health	Algorithm-dependent estimate; explain calculation method before making warranty claims.
Pack Volt.	Total battery-string voltage	Compare with series configuration and historical operating state.
Max / Min Cell V.	Highest and lowest active cell voltage	The difference is an instantaneous consistency indicator, not a standalone diagnosis.
VDiff.	Maximum minus minimum cell voltage	Interpret against SOC, current, temperature and duration.
Online Cell Volts	Number of reporting cell-voltage channels	Exclude zero/unconfigured channels from analysis.
Online Thermistors	Number of reporting temperature sensors	Exclude -41°C placeholder channels from analysis.
ChgOV	Charging over-voltage alarm	Review cell voltage, charge limits, inverter settings and alarm thresholds.
Relay Status	Reported contactor/relay states	Decode each bit against the product protocol before external publication.
Insul. Resis.	Insulation-resistance measurement	“invalid” means unavailable/not valid, not zero resistance.

Reliable data interpretation

• Analysis uses configured channels that are actively reporting to the platform.
• Zero-voltage and -41°C placeholder channels are recognized as unavailable inputs and excluded from valid-channel statistics.
• Unavailable insulation-resistance readings are displayed as “invalid” and are not interpreted as zero.
• Raw millivolt fields are converted to customer-friendly volts while retaining units and precision.
• Commissioning confirms field mapping, connected sensor counts and current sign convention.
• Historical records provide the operating evidence technicians need to evaluate conditions in context.

OPERATIONAL CONTEXT  Displayed values should be interpreted with SOC, current, temperature, duration and system state. Platform analytics support diagnosis and service decisions; final actions remain subject to the configured battery, inverter and site operating limits.

Connected intelligence for energy storage

SEE EVERY CELL. UNDERSTAND EVERY EVENT.

Cloud intelligence for safer, more serviceable energy storage.

The LUMO Cloud Monitoring Platform gives installers, system owners and service teams a live view of battery performance from pack level down to individual cells. Connected operating data brings pack voltage, current, SOC, SOH, cell-voltage spread, temperature, relay state and alarm history into one remote service environment.

Instead of relying on a single site visit or the latest alarm code, LUMO preserves the operating story behind every event. Time-stamped telemetry, alarm duration and recovery records, daily operating statistics and synchronized historical charts help technicians understand what changed, when it changed and how the battery responded.

Key platform advantages

• Cell-level real-time visibility – monitor individual cell voltage and active temperature sensors, not only pack totals.
• Faster remote diagnosis – compare live status, alarms and historical trends before sending a technician to site.
• Traceable protection events – preserve alarm level, start time, duration, end time and recovery status.
• Historical event replay – align current, pack voltage, cell spread, SOC and temperature on the same time window.
• Data foundation for remote balancing – use complete charging-process data to support personalized balancing decisions.
• Support for Level 4 service analysis – retain the context around smart-breaker protection events and abnormal depletion.

Short website summary

LUMO CLOUD  A connected monitoring and service platform for commercial and industrial energy storage. See pack and cell data in real time, trace every alarm, replay historical events and give service teams the evidence they need to protect battery health and resolve issues faster.

Built for customer confidence

• Monitor pack, cell and thermal performance from one unified remote interface.
• Review alarm timing, duration and recovery status before dispatching service resources.
• Use synchronized historical trends to distinguish isolated events from persistent conditions.
• Support proactive battery-health management with evidence-based balancing and service decisions.