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－62－
Integrated Battery Management System Combining Cell Voltage Sensor and Leakage Sensor
SOC100%
Over-charge risk
Over-discharge risk
Estimation error
Estimation error
Working range
Over-charge risk
Over-discharge risk
Estimation error
enlarge
Estimation error
Working range
0%
chargeupper limit
dischargelower limit
Estimation accuracyLOW
Estimation accuracyHIGH
Shingo TSUCHIYA＊１
automobiles, the cost of the battery, available occupant
space, and the driving range have become issues, and
thus making further evolution of the BMS is required.
This paper introduces new technical contents in
BMS development that are available to achieve cost
reduction, downsizing, high precision cell voltage
detection and high efficiency for increasing driving
range, combined with improvements in safety
protection reliability of the lithium-ion battery with
which there are inherent smoke and fire risks.
2. Integration of System with High Voltage
A convent ional BMS consis ts of mul t ip le
components: a battery control unit (Batt-ECU); cell
voltage sensors (CVSs); and a leakage sensor.
Since the number of battery cells is large, an
example would be a CVS arranged for each battery
module of 12 cells in series connection, where the
cell information measured by the CVS is sent to
the Batt-ECU via communication bus, and each cell
is controlled by the Batt-ECU, such system being
called a distributed BMS.
However, the use of a distributed BMS causes
substantial increases in vehicle cost with the
increased unit cost due to the use of multiple CVSs
and electric harness for inter-unit communication.
In consideration of this situation, an integrated
BMS has been developed, greatly reducing costs
by combining the Batt-ECU, CVSs and a leakage
sensor into one unit (Fig. 2).
＊１ BMS Development Department, R&D Operations
※ Received 28 August 2017
1. Introduction
The issues of global warming and the tightening
of legal res t r ic t ions have caused the market
environment to move towards widespread use and
expansion of electrically driven vehicles.
Hybrid e lect r ic vehic les (HEVs) and zero
emiss ion vehic les (ZEVs) are equipped wi th
rechargeable lithium-ion batteries (LiBs) to drive the
traction motor and accessories. In order to expand
the energy density of the high voltage battery and
maximize battery performance, a battery management
system (BMS) using technologies of high precision
cell voltage detection and highly efficient energy
loss reduction, is indispensable (Fig. 1).
Today, various HEVs and ZEV’s are released
by vehicle manufacturers, and it can be said that
electrically driven vehicles have entered into a
period of expansion.
However, as a consequence of the electrification of
Technical Digest
Integrated Battery Management System Combining
Cell Voltage Sensor and Leakage Sensor ※
Fig. 1 Maximize effective use of battery performance
TechnicalDigests
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Keihin Technical Review Vol.6 (2017)
Li-ion leakage detection
leakage sensorcell voltage sensor
battery ECU
leakhigh voltageconnection
control
battery residualquantity info.
PCU
MG ECU
BMS
battery cooling control
systemintegration
Cellvoltage
temperature
current
mask processing according to the voltage fluctuation
state of the battery, have been introduced in order to
distinguish battery transient voltage fluctuation from
leakage resistance fluctuation, and thus detection
accuracy has been greatly improved (Fig. 4).
Expanding these techniques to various cell
numbers and into the platform, a BMS that can deal
with various battery cell number variations has been
developed (Fig. 5).
Fig. 2 Integrated BMS with system diagram
leakageresistance
FG
FG(Frame GND)
levelconversion
battery voltagedetection
Large peak value = large leakage resistanceLow peak value = low leakage resistance
BPF
MPU
Signalamplifier
referencesignal
generator
FFT processingresistancecalculation
mask processingexternal BMS
LiB
Fig. 3 Leakage detection block diagram
BMS passing voltagebattery transient voltage fluctuation
starting voltageovercurrent cut-off
induction noise
inverter SW noise
1st, 2nd ordercommon mode noise
sudden acceleration
strong regenerative
Fig. 4 Effectiveness of FFT & mask in image
PCB for BMS
Lower case
Upper cover
Fig. 5 BMS for 48 cells (left) and 96 cells (right)
Furthermore, with regard to the cell voltage
monitoring part of the CVS, a new circuit has been
developed in which a level shift type flying capacitor
circuit configuration based on conventional discrete
components has been modified, and the new circuit
has been designed whereby the input protection
which was necessary for each cell can be conducted
for multiple cells. With this technique, the protection
components are minimized while also reducing leakage
current, and functional integration of the cell voltage
monitoring part into a one chip IC was also achieved.
In comparison with the conventional unit, the CVS part
was downsized by 84% and cost was also reduced.
This IC is normally called LiB-IC, it has the multiple
functions, such as cell voltage detection, cell balancing,
fault diagnosis, inter-IC daisy chain communication.
Moreover, with regard to the function of leakage
detection between the high voltage battery and the
vehicle body frame ground, the conventional expensive
DC insulation detection circuit using photo MOS
relay has been with an AC insulation detection circuit
based on capacitive coupling of capacitors, resulting
in a size reduction of 42% in comparison with the
conventional unit and lower cost (Fig. 3). Since AC
insulation detection approach uses capacitive coupling
to form a differentiating circuit, there exists issues
that it is easily influenced by disturbance such as
battery transient voltage fluctuation due to acceleration
and deceleration of the vehicle, and the detection
accuracy of the leakage resistance value is not stable.
Techniques such as FFT (fast fourier transform)
processing by the MPU (microprocessor unit), and
－64－
Integrated Battery Management System Combining Cell Voltage Sensor and Leakage Sensor
: hindrance factor for accuracy
harness disconnectiondetection
correction learning
after correctiontrue value before correction
cell voltage
cell balancing
Cel
l vol
tage
det
ecte
d [V
]
Cell voltage [V]
gain
ideal line
beforecorrection
aftercorrection
offset
3. Improvement in Cell Voltage Detection Accuracy
Monitoring cell voltage with high accuracy,
known as one of the main functions of the BMS,
was also raised as a topic of our development.
Although cell voltage measurement is performed
by the LiB-IC, it is necessary to execute multi-task
processing simultaneously such as cell balancing
control, harness disconnection detection control, and
various self-diagnoses within the time specified. A
high speed and high precision LiB-IC control system
has been established during this development. As
examples: disconnection detection time has been
shortened to 1/10 of the conventional time by using
original control which greatly increases the electric
charge removal amount remaining in cell voltage
monitoring area at the time of harness disconnection;
and cell balancing time has been shortened to 1/2 of
the conventional time by controlling the increment
or decrement of the cell balancing current amount
according to the cell voltage and temperature.
As an original technique to improve accuracy, an
individual learning function of the correction factor
has been developed, i.e. after acquiring the LiB-IC
detection values for cell voltage at multiple points
in the production process, the gain offset portion of
the cell detection value is calculated, and stored in
a microcomputer non-volatile memory. By means of
such microcomputer correction learning, an accuracy
correction technique has been established so that
the initial variation of a mounted component can be
cancelled in the production process (Fig. 6). Stresses
on a chip due to the assembly of the vehicle body
after shipment of the BMS and environmental
change has also been considered. Taking secular
changes into account, to maintain a high precision of
cell voltage during the long-term product warranty
period has been realized.
On the other hand, control of cell balancing
Fig. 6 Schematic of correction of cell detection accuracy
Fig. 7 Cell detection accuracy correction for voltage drop by wiring resistance
and harness disconnection detection is mentioned
as a hindrance to cell voltage accuracy. Since a
weak current flow is used to execute control and
detection, this weak current causes a voltage drop
in the wiring, leading to accuracy deterioration to
the millivolt order. As a measure for this, techniques
have been established to estimate the amount of
voltage drop in the wiring by a microcomputer and
perform correction learning, resulting in successful
technique development for cancel l ing wir ing
influence of several mΩ units (Fig. 7).
In order to achieve further improvement of
accuracy, the chip mounting layout was also been
investigated. The LiB-IC is mounted in a rotated
posi t ion at an angle of 45 degrees to reduce
variation in inter-cell detection. This makes it
possible to equalize and minimize the detection
wiring for each cell from the LiB-IC to the ECU
connector, resulting in improvement of detection
TechnicalDigests
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Keihin Technical Review Vol.6 (2017)
Main MPU SUB MPU
DCLS
SPFM
LFM
Core Core
calculationresult
comparison
monitoringfunction
monitoringfunction
output forcharging path
shutdown
two-waycommunication
connector
LiB-ICLiB-IC
connector
chargeupper limit
dischargelower limit
Voltage [V] battery characteristic curve
reducing error
reducing error
conventional error
conventional error
conventional SOC
Improved SOC
Fig. 9 Expansion of battery SOC range
Fig. 8 LiB-IC layout design and implementation
accuracy (Fig. 8).
Furthermore, in order to remove high frequency
noise components caused by bat tery vol tage
fluctuation and other factors, we have succeeded in
improvement of the dynamic detection accuracy, and
downsizing of the analogue filter component of the
cell input area by increasing the sampling rate and
using digital filter processing.
Such techniques developed for improving cell
voltage detection accuracy, has enabled us to
expand the battery state of charge (SOC) range by
7.8% (source: in-house investigation in 2017), thus
contributing to an increase of driving range (Fig. 9).
risk of smoke or fire exists if overcharging occurs.
It was necessary to set the safety goal for cell
overcharge to ASIL D, which is the ranking at the
most stringent safety level, and thus incorporate
various safety mechanisms into the BMS.
Requirements for achieving ASIL D are, a PMHF
(probabilistic metric for random hardware failures)
value lower than 10FIT, a SPFM (single point fault
metric) value higher than 99% and a LFM (latent
fault metric) higher than 90%.
In the unlikely event that i t is judged that
the cell voltage has risen to overcharge detection
voltage, it is necessary to shut down the battery
charging path and stop the system safely, therefore
a mechanism to ensure that the BMS never fails to
detect overcharging must be constructed.
As an approach to ISO 26262, the development
process was divided into vehicle manufacturer area
and the supplier area, and development has been
performed from PART 4, the system level.
As a safety mechanism to the cell voltage
p roces s ing and comput ing pa r t a f t e r s a fe ty
analysis of cell overcharge, an MPU with a DCLS
mechanism in the main MPU was adopted and the
reliability of the core was improved to satisfy SPFM
requirements. Additionally, a mutual monitoring
function using a sub-CPU was provided to satisfy
LFM requirements, and a mechanism for shutdown
of the charging path to safely protect the system
when a malfunct ion occurs in the MPU was
established (Fig. 10).
When the BMS works correctly, it is impossible
Fig. 10 MPU safety mechanism
4. Approach to ISO 26262
Since lithium-ion batteries use volatile and
flammable organic solvents in the electrolyte, the
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Integrated Battery Management System Combining Cell Voltage Sensor and Leakage Sensor
overcharge
overcharge
<BMS function failed>redundant backup function
V sensor
V sensor
V sensor failure
computingjudging
computingjudging
computingjudging
relaydrive
relaydrive
PCU
vehicle stops(safety)
→ vehicle stops (safety)
limp-homeperformance
MOFF
PCU MOFF
<BMS works correctly>
Redundantmonitoring
for any overcharge to be overlooked, but safety
cannot be guaranteed if the cell voltage is read
lower than the true value for some reason, such as
a component failure. For mechanisms such as when
the true voltage value cannot be detected, the self-
diagnosis function of the BMS identifies the failed
part, and cell overcharge is continuously monitored
by a backup sensor with redundancy, having been
constructed to improve each individual self-diagnosis
detection rate and thus make it possible to satisfy
safety target failure rates. If an abnormality occurs
in the system, limp-home performance is provided
that allows the vehicle to evacuate to a safe place
by preventing an unnecessary sudden stop of the
vehicle (Fig. 11). The mechanism whereby self-
diagnosis functions are prepared for shutdown of the
battery charging path so as to definitely interrupt
charging when facing the risk of overcharge has also
been constructed to ensure safety.
As mentioned above, to protect the system even
when a function failure occurs, a BMS equipped
with various safety mechanisms has been developed,
and ASIL D requirements have been achieved.
Because the ISO 26262 development process
requires certification by internal and external
assessment, the system safety of the BMS has been
proved in PART 4 (system), PART 5 (hardware),
and PART 6 (software) of the V-model development
cycle.
Fig. 11 Backup function for cell voltage monitoring failure
5. Outlook for the Future
Multiple integrated BMSs with improved cost,
performance and safety have been developed
corresponding to variations of battery cell number.
However, systems using a battery as a main
power source in ZEVs are likely to incorporate
batteries of even larger capacity. Because the sensing
harness is attached to run from each battery cell to
a particular area of the BMS, increase in harness
cost and expansion of equipment space needed will
become issues. In such a case, it is considered that
there may still exist the needs of a distributed BMS
equipped with CVS for each battery module as in
conventional battery units. The appropriate use of
an integrated BMS or a distributed BMS according
to vehicle needs will need to be considered in the
future.
With the expansion of automotive electrification,
there exists the reality that no ZEV has a driving
range at the same level as HEVs or gasoline-only
vehicles. Even if batteries are laid in the whole
vehicle underfloor area, the battery capacity is still
insufficient, that is to say, enlargement of battery
capacity causes many problems such as mounting
space and weight increase of the battery itself.
Along with progress of downsizing and reducing
the weight of the battery itself, the improvement
of battery l ife and energy efficiency by BMS
control will become the most important area for
development.
Regarding the current battery capacity estimation
accuracy, when safety is taken into consideration,
only a small amount of the entire battery capacity
is used, and battery capacity is available to the
limit that remaining power allows, so a BMS that
maximizes battery performance by using up the
battery capacity to the maximum extent is required.
For this reason, we believe that progress in
techniques for highly accurate estimation of the
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Keihin Technical Review Vol.6 (2017)
Author
S. TSUCHIYA
With this development, we provided a smaller,
less expensive and highly reliable BMS for factory
production electrically driven vehicles. BMS players
in the market tend to increase year to year, bringing
about more and more competition. We will continue
our efforts to further the technological evolution of
the BMS, and contribute to the future of humanity.
Finally, I would like to express my deepest
gratitude to everyone who has cooperated with this
development. Thank you very much! (TSUCHIYA)
battery SOC and SOH (state of health) based on the
battery voltage and current values, etc., detected by
the BMS is important, thus expanding the use of the
battery SOC and increasing driving range (Fig. 12).
Although it is possible to accurately estimate
when the amount of battery charge or discharge is
stable, high precision estimation which conforms
to the complicated conditions of battery charge and
discharge during vehicle running is a development
theme in the future.
With the expansion of automotive electrification,
battery related technologies have progressed from
the introduction stage through to the growth stage.
There is still possibility for energy efficiency
improvement by means of control techniques
together with technology advances in the battery
itself, and further innovations in the BMS can
largely contribute to the improvement of vehicles.
We wish to spend more efforts into battery condition
monitoring technologies in order to contribute to the
improvement in convenience of electric vehicles and
reduction in CO2 and global warming.
Fig. 12 Relationship between BMS and SOC, SOH
cell voltagedetection (Vcell)
cell voltage truevalue
battery currentdetection (Ibatt)
battery internalimpedance Z
OCV
SOC = OCV (cell voltage true value) = Vcell (ccv) - Z × Ibatt
LiB-IC
CPU
SOHestimation
SOCestimation
BMS
BMSmeasurement
value
currentsensor
battery current
CCV
