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Request for Proposal
Status: RFP is Open

Diagnosis for On-board Li-Ion Battery Degradation

Request Number
RFP_2020_0005
Due Date
Mar 2
Program Manager

Opportunity
Joint/contract development, technology licensing, consulting

 

Timeline
Phase 1: Verification of principle within 1 year
Phase 2: Verification on real machine within 2 years

 

Financials
Details to be negotiated based on proposed technologies

 

How to  Apply
  • Click "Respond", complete the form to the extent possible, and submit along with other attachment files available. 
  • After creating your account for NineSights, your draft will be automatically saved and you can resume later from "Control Center". Please note you do not submit confidential information at this process.
  • This request for proposals in PDF format is available here.
SOLUTION PROVIDER HELP DESK
If you have any questions or request, please feel free to contact us at: phd2@ninesigma.com

RFP Title

 

Diagnosis for On-board Li-Ion Battery Degradation
RFP Description

NineSigma, representing a major auto parts manufacturer, seeks technology for fast diagnosis of on-board lithium-ion (Li-Ion) battery degradation. Especially, a measurement approach to battery capacity and internal resistance using small scale charge-discharge in a short time is anticipated.

Key Success Criteria

Target on-board Li-Ion battery

  • Electrode type: NMC/LTO or carbon/LFP
  • Capacity: approx. 72 Wh/cell
  • Maximum output: 300 W/cell
  • Output time: several tens of minutes
  • Assumed operating temperature: −30°C to 60°C

 

Technological requirements

Capable of rapidly diagnosing the degradation degree of on-board Li-ion battery.

  • Assumed measurement items: battery capacity and internal resistance or output power
    • The measured values must be presented
  • Measurement time: within several seconds
  • Measurement accuracy: ±5% or less is desirable
  • Capable of explaining measurement mechanism and results from a battery chemistry perspective
    • Capable of explaining temperature and time dependency of degradation
    • Desirable to explain both degradation phenomena caused by repeated use and aging

Not all of the above requirements need to be met at this time. Proposals are welcome if there is some possibility of meeting them by 1–2 years of additional development.

Possible Approaches

The followings and combination there of are examples the client expects. Other technological solutions are broadly welcome if they are on-board compatible.

  • Approach to rapidly measuring battery capacity and internal resistance by charging or discharging of some watts
  • Improvement of diagnostic accuracy and speed by machine learning or big data analysis of a battery degradation model
  • Miniaturized internal resistance measurement technology and devices
Approaches not of Interest

The following technologies are not of interest:

  • Measurement technology that needs equipment unsuitable for automotive
  • Technology to promote the degradation of Li-ion battery
  • Prediction technology based on the model using only measured data tables
Items to be Submitted

Background

The use of Li-ion battery is crucial in the future to deal with increased vehicle electrification and automatization. As the key to using on-board Li-ion batteries, the client has been engaged in the development of battery degradation diagnosis, especially technology to rapidly measure the capacity and internal resistance of a battery. Unfortunately, no promising solutions have yet been found. Since Li-ion batteries grow popular in various industries, and approaches to degradation diagnosis technology are widely studied, the client hence decided to seek technology proposals to accelerate research and development in-house.

 

Notes on Response

Proposal shall have clear points and should not include confidential information. Supplemental files may be submitted in addition to the proposal.

 

Response evaluation

The client will evaluate all responses with the following criteria.

  • Overall scientific and technical merit
  • Approach to proof of concept or performance
  • Economic potential of concept
  • Realism of the proposed plan (action items, timeline, roles, deliverables, cost estimation)
  • Potential for proprietary position
  • Respondents’ capability and related experiences

 

Anticipated Project Process

After the submission due date, the client will review all submitted proposals. NineSigma will send the review results to each proposer 6-8 weeks after the due date. The client possibly asks clarifying questions before selecting the most suitable candidates for collaboration. The client will select best candidates through evaluations. During the selection process, the client may conclude NDA with selected respondents, seek further information disclosure, and discuss specific development targets or potential opportunities.
The client will conclude necessary agreements with the selected respondents and move to the advanced development phase. Specifics of any collaboration will be determined through consultation with the concerned parties.

 

Preferred Collaboration Types
Area of Interest