Last updated: Feb 2020 by Narasimhan Santhanam
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t is a part of EV Next’s EV Perspectives.
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Introduction
A battery management system (BMS) is the brain behind the battery pack. It monitors and protects cells in a battery pack. The BMS market is diverse, with multiple applications that use a large number of battery packs. Rising demand for electric vehicles, energy storage systems, and aerospace and defense equipment powered by batteries make BMS an important component in daily life. BMS has evolved from a mere monitoring unit to an advanced, intelligent unit that decides what a battery should do at different modes of operation. The study also analyzes the application sectors that employ these batteries, mainly automotive, healthcare, telecommunications, consumer electronics, and utility-grid, and the innovations occurring in each sector.
Intelligent Cell Monitoring
During the charging and discharging of an EV battery, it is imperative that each cell within the battery pack is closely and accurately monitored because any number of out-of-spec conditions can, at a minimum, quickly cause internal damage of the battery and vehicle or threaten the safety of the vehicle’s occupants. EV batteries contain the energy equivalent to a small explosive. Over-voltage or under-voltage conditions can lead to thermal runaways that might cause a battery failure.
A battery monitoring integrated circuit (BMIC) or cell-balancer device is typically assigned to monitor the voltage of each battery cell in a module, the temperature of various points in the module and other conditions. This data is reported to a cell management controller (CMC) and, depending on the complexity of the system, on to higher-order processing elements, such as one or more battery management controllers (BMC). The precision of these measurements and the frequency of the communications from the BMIC to the CMC and BMC is key to detecting a condition of concern early on and taking corrective action before it becomes hazardous.
Intelligent Battery Management
Depending on the complexity of the vehicle, several intelligent microcontrollers (MCUs) oversee and manage various critical tasks with regards to the battery and the power subsystem. Usually, these MCUs contain multiple processing cores. Some may be comprised solely of general-purpose reduced instruction set computing (RISC) processors, such as ARM cores, while others, which are responsible for tasks that are mathematically intense, usually feature one or more digital signal processing (DSP) core, like TI’s C28x DSP cores, so that none of the cells are charged above 4.1 V. This would reduce the stress placed on CMCs, working in concert with BMICs, play an important role in ensuring the performance of the battery and its useful lifespan.
Intelligent Battery Charging
Charging and discharging the battery efficiently is important as it avoids thermal runaways or other conditions that would either reduce the battery’s capacity or its lifespan. To do this, requires a certain amount of intelligence in the controlling MCU since the parameters of the battery itself will change over time. The MCU responsible for the actual charging of the battery must be able to quickly adjust and adapt in real-time to the battery’s changing properties, like oxidation on the terminals, cell voltages and others. During charging in particular, the MCU must be able to respond quickly to overvoltage conditions. Otherwise, it might cause the battery to overheat and catch on fire.
When designing battery charging modules such as an on-board charger, higher-order microcontrollers that feature DSP cores and specialized coprocessors or hardware-based accelerators can be deployed to meet specific real-time operational needs for closed-loop control of on-board charging input current, intermediate DC bus voltage, battery charging current and battery terminal voltage. These control loops require the use of computation intensive algorithms such as a PID controller or two pole two-zero compensators. A MCU with a DSP core(s) running special instruction sets supporting special trigonometric math operations can significantly reduce the number of processor cycles needed for these algorithms.
Read more on the EV Battery ecosystem from: EV battery Innovations | Components of BMS | FCEV Trends | FCEV Indian Efforts | Anode/Cathode R&D | Li-ion Battery Trends | BMS Innovations | Indian Battery Manufacturers | Cost of Li-ion Batteries | Anode Materials in 2020-2030 | Key Drivers shaping Battery Chemistry |
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See also the blog posts:
- Research Trends Li-ion Anode/Cathode Material – NMC, LFP, NCA Chemistries for Lithium-Ion Batteries
- Technologies and Innovations in EV Industry – Better Batteries, Lighter Cars, Faster Charging
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