Niall Lyne, Renesas Electronics Corporation
BMS designers have learned how to optimize BMS measurements and achieve high performance in an electrically and environmentally hostile automotive setting. The designers focus is still on cell measurement requiring millivolt and milliamp accuracy, and time-synchronizing these voltage and current measurements to calculate impedance.
The BMS must also assess validity of each measurement, as it needs to maximize data integrity, and identify, differentiate and act on errors or questionable readings. BMS IC manufacturers have also learned and evolved to provide the key architectures that meet comprehensive monitoring,stringent safety, reliability and performance requirements of electric vehicle (EV) battery management systems.
The BMS IC selection today is also critical for boosting the lifespan of the battery packs, as batteries will degrade through normal operation. While operating, the battery pack state of health (SOH) accuracy allows the vehicle’s battery management electronics to make decisions about battery usage and power delivery to optimize the remaining life of the pack. A key element of battery management design is directly affected by the battery management IC’s ability to maintain its precision measurement accuracy over the vehicle’s service life. Any drift or instability in battery cell measurement directly influences the vehicles range and battery life, which in turn affects the automaker’s warranties and cost of ownership.
Li-ion batteries used to power EVs typically offer 8-10 years warranty. After that, batteries are considered inappropriate for automotive traction applications but may still have 80% of their original capacity. This will also assist, for the second life use, where a used battery pack from an automobile can be passed on to other self-consumption battery applicationswith a specified remaining lifespan.
For automobile manufacturers, successful BMS implementation requires careful selection of the BMS IC at the outset of system design, and that requires understanding the differences in measurement accuracy and stability between the various IC vendor offerings in a harsh electromagnetic interference (EMI) environment, with high voltage batteries and Inverter noise, across the entire operating environment and life of the vehicle.
The four most important criteria for a good Li-ion monitoring system are:
Lithium-iron phosphate batteries benefitsmaller packs due to their low internal impedance. These cell types make it necessary for system engineers to detect small changes in cell voltage as the battery discharges. Measuring these small cell voltage changes requires a sophisticated combination of analog front end (AFE), accurate and stable voltage reference, and precision analog-to-digital converter (ADC), which is a considerable design challenge for BMS IC designers.
Key Elements in a Multi Cell Balancing IC
At the core of any BMS IC is a precision reference. The types of reference topologies employed vary, although bandgaps tend to be the most commonly used due to their optimal trade-off in accuracy versus die area, and accuracy across temperature. For example, the ISL78714 multi-cell Li-ion battery manager IC uses a precision bandgap reference design that has a solid track record and is well suited for demanding automotive applications. The technology is stable, mature, well characterized, and has been optimized over many years of use. This is a key consideration when designers make vehicle battery-life calculations that directly influences a carmaker’s warranty and cost of ownership metrics.
Along with a precision reference, another key functional block for measuring accuracy is the ADC, as the main cell-voltage-measurement block. Two of the most popular and commonly used types of ADCs are successive approximation register (SAR) and delta-sigma. Having the fastest sampling rate of the two technologies, the SAR offers high-speed voltage conversion and excellent noise immunity but tends to require a larger die area. SAR ADCs also offer the best combination of data acquisition speed, accuracy, robustness and immunity to the effects of EMI.
IC designers also like delta-sigma ADCs as they typically require less die area and are relatively easy to implement. However, they tend to be slower as they use a decimation filter, which reduces the sample rate and data acquisition speed. Another consideration when implementing delta-sigma ADCs is their tendency to saturate when subjected to EMI, which may cause a delay (typically three full conversion cycles) in the accurate reporting of cell voltages.
The individual cells interface is managed by the AFE, which comprises input buffers, level shifters and fault detection circuitry. The AFE is key to handling hot plug transients when the cells are initially connected to the BMS. The ISL78714 BMS IC is designed with a fully differential AFE that enables negative input voltages (±5V) to be measured without affecting the adjacent cell measurements. This is advantageous in systems where bus bar interconnection is required. To improve robustness under transient conditions, an external low-pass filter is added to the cell voltage inputs.
The input filtering requirements have been optimized for maximum EMI and hot plug immunity, without compromising speed or accuracy. By contrast, ICs that use a bipolar rather than charge coupled AFE can have their accuracy and long-term drift substantially degraded by the component values selected for the external input filter. Figure 1 shows a simplified diagram of the BMS IC’s three functional blocks and their interconnection.
The combination of a stable and linear bandgap reference, SAR ADC and fully differential AFE gives a multi-cell Li-ion battery manager fast data acquisition capability combined with robustness and precision accuracy. Rather than relying simply on the measured accuracy values when it leaves the factory, the BMS IC’s high accuracy is independently verified after mounting on a printed circuit board (PCB). Figures 2a and 2b displays the IC’s accuracy over a range of cell voltages and temperatures. This is of critical importance to battery system designers, as they require a system error budget for the vehicle’s service life, and-must be able to factor in reliable and predictable accuracy figures.
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Figure 2a & 2b. Readings collected from 30 BMS boards tested 1,000 hours after assembly
Therefore, a careful examination is recommended, and a detailed comparison should be made between each IC vendor’s data sheets, particularly in the areas of accuracy, data acquisition speed, and input filter requirements, including their effect on accuracy.
PCB Layout and Configuration Considerations
Soldering induces stresses across a PCB, that in turn flex the BMS IC in the X and Y plane, resulting in sub-atomic stress in the silicon’s properties, which influences the IC’s behavior. Since the reference is a critical part of the measurement circuitry, any variation in its characteristics has a direct effect on the accuracy of the ADC. This is a well-known and understood phenomenon in the precision IC industry, and IC designers make allowances for this by carefully placing sensitive circuitry in the die areas less likely affected by soldering and other manufacturing stresses.
Alternatively, there are more costly reference design techniques available to IC designers, such as placing a separate reference die within the same IC package or using a separate discrete reference IC. No matter which IC technique is used, the PCB design and manufacturing stage are both critical, so precision IC layout techniques and careful consideration for IC mounting and soldering profiles can help mitigate any issues.
BMS designers who, for example, follow the ISL78714’s recommended PCB layout guidelines and soldering reflow profiles, will see that the IC’s board-level cell reading accuracy and long-term drift characteristics are both logarithmic and predictable. The IC’s long-term drift performance is obtained from actual laboratory testing at 25°C and accelerated life testing. Accuracy over life is a vector addition of initial board level accuracy and lifetime drift, e.g., sum mean values and RSS standard deviations. Figure 3 represents the results in a typical cell reading error over 15 years of service life.
Accuracy summary Min Typ Max
Lifetime accuracy at 3.5V per cell at ±3σ -3.78 -0.63 2.10
Lifetime accuracy at 3.5V per cell at ±6σ -6.26 -0.63 4.16
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Figure 3. Initial board level cell error at ±6σ(post solder) Vs. lifetime
A key element of battery management design is factoring in battery performance, which is directly affected by a BMS IC’s ability to maintain its precision measurement accuracy over the vehicle’s service life. Any drift or instability in battery cell measurement directly influences the vehicles range and battery life, which in turn affects the carmaker’s warranties and cost of ownership. There are various BMS ICs available to choose from with different accuracy measurement topologies and technologies, so system designers must carefully consider their IC selection and use. Optimizing BMS design and understanding the underlying differences in measurements, schemes and topologies, and their interrelationship is critical in selecting the most appropriate BMS IC for their automotive EV application.