Wireless BMS Noise-Immunity Mode for Interference and Jamming
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Wireless battery systems in electric vehicles face significant challenges due to interference or jamming, which can disrupt communication and pose safety concerns, as existing technologies lack sufficient immunity to noise and interference.
Innovation Solution
Implementing a noise immunity operating mode that switches from a normal operating mode to a high-immunity mode by increasing the number of transmitted bits per bit of information, using techniques such as Direct Sequence Spread Spectrum (DSSS) or Forward Error Correction (FEC) codes, to enhance resilience against interference and jamming.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system transmits more bits per information bit (increasing lengthening factor), then noise immunity improves, but data rate decreases
Solution Approach 1:
The system dynamically switches between normal operating mode and noise immunity operating mode based on detected environmental conditions. When noise is detected, the system transitions to a higher lengthening factor (more chips per bit) to improve reliability, and switches back to normal mode when conditions improve, thus adaptively balancing reliability and data rate.
Solution Approach 2:
The system changes the lengthening factor parameter from a first value in normal mode to a second value (greater than the first) in noise immunity mode. This parameter change increases the number of chips per information bit, thereby improving noise immunity at the cost of reduced data rate during noisy conditions.
2Reliability
If the system uses heavily-coded signals with multiple chips per bit, then interference immunity improves, but transmission speed decreases
Solution Approach 1:
The system employs dynamic mode switching between normal operation and noise immunity operation. During normal conditions, it uses standard coding for high-speed transmission. When interference or noise is detected, it switches to heavily-coded signals with multiple chips per bit to achieve better interference immunity, thus dynamically balancing speed and reliability based on environmental conditions.
Solution Approach 2:
The system adjusts the coding parameter (number of chips per information bit) based on operating conditions. In noise immunity mode, it increases this parameter to provide better interference protection, while in normal mode it uses lower coding overhead to maintain higher transmission speed.
3Reliability
If the system reduces data rate to increase coding overhead, then resilience to jamming improves, but communication efficiency decreases
Solution Approach 1:
The system implements dynamic adaptation by monitoring the wireless environment and switching between operational modes. When jamming or significant noise is detected, it reduces data rate by increasing coding overhead (more chips per bit) to improve resilience. When conditions are good, it switches to higher efficiency mode with less coding overhead, thus dynamically optimizing the balance between resilience and efficiency.
Solution Approach 2:
The system changes operational parameters including data rate and coding overhead based on detected environmental conditions. In noise immunity mode, it increases coding overhead and reduces data rate to improve jamming resilience, while in normal mode it maintains higher communication efficiency with lower overhead.
Data Source
Figure 1
Figure 2
AI summary
Techniques to improve the immunity of wireless battery systems by transmitting heavily-coded signals, e.g., using multiple chips of a sequence for each bit of information, to trade data rate for interference or jamming immunity as a response once a noisy environment is identified. The techniques provide the system with a noise immunity operating mode (or high-immunity transmit and receive mode) that can improve resilience to interference or jamming by reducing the data rate. One option for reducing the data rate is by slowing down the transmission bit rate to reduce the occupied transmit bandwidth to minimize the probability of collisions with interfering signals. Another option is though digital coding methods using Forward Error Correction such as Convolutional Coding, Reed-Solomon Coding and Turbo coding. A third option is with RF spread spectrum techniques such as Direct Sequence Spread Spectrum (DSSS) or Frequency Hopped Spread Spectrum (FHSS).