Technology

Our breakthrough is especially significant for NiMH batteries, where accurate diagnostics has long been considered impractical. Even greater potential is expected for lithium-ion batteries.

There are two techniques for diagnosing battery degradation, one using AC the other using DC.

Designed for real-world vehicle environments, our DC-based technology enables robust onboard battery capacity estimation with high noise immunity.

	*EIS testing method 1**	(Patented)
Expected prediction accuracy	50%〜60% (Off-board, Not applicable for On-board)	90%(On-board diagnosis) 〜 95%+(Off-board)
Required time	Typically 5 to 15 min.	3 min.(On-board) 〜 2min.(Off-board)
Required resolution of data.	1.00[mΩ] or less	Depend on the vehicle sensors(On-board) 〜 12[mV]・12[mA] or less. & 100[mSec] or less. (Off-board)
Influence of the DUT’s SOC status	Affected by	Not affected
Acquired data sample.		(Not disclosed)
Calculation	Impedance [Z]	Capacity [Ah]
Approach	Steady-state Analysis	Transient Analysis
SMU cost and Current-type (40 modules case for Off-board)	Approx. $360K (AC)	Approx. $6K (DC)

95%+ Accurate Battery Capacity Estimation in Minutes

**EIS testing method *1**

(Patented)

Expected prediction accuracy

50%〜60% (Off-board, Not applicable for On-board)

90%(On-board diagnosis) 〜 95%+(Off-board)

Required time

Typically 5 to 15 min.

3 min.(On-board) 〜 2min.(Off-board)

Required resolution of data.

1.00[mΩ] or less

Depend on the vehicle sensors(On-board) 〜 12[mV]・12[mA] or less.
& 100[mSec] or less. (Off-board)

Influence of the DUT’s SOC status

Affected by

Not affected

Acquired data sample.

(Not disclosed)

Calculation

Impedance [Z]

Capacity [Ah]

Approach

Steady-state Analysis

Transient Analysis

SMU cost and Current-type (40 modules case for Off-board)

Approx. $360K (AC)

Approx. $6K (DC)

*1 There are many variations of the EIS method, the above is just one example

A typical example of the use of AC is the EIS (Electrochemical Impedance Spectroscopy) test method.

Conventional EIS methods faced a fundamental limitation: once current is applied, the battery’s internal state immediately begins to change, reducing prediction accuracy.

Rather than avoiding this dynamic behavior, our patented EVANS algorithm analyzes the changes themselves — enabling fast and highly accurate battery diagnostics.

In real business, prediction accuracy has the greatest impact on profitability