Which Electric Vehicle battery technology offers the best long-term value for Indian consumers?

Compare LFP vs. NMC battery technologies in electric vehicles, analyzing energy density, thermal stability, cycle life, replacement costs, and suitability for Indian climate conditions.

# Aplly.xyz Case Study Submission

## Title
Which Electric Vehicle battery technology offers the best long-term value for Indian consumers?

## Type
Multi-Criteria Product Comparison

## Difficulty
Intermediate

## Estimated Time
60 minutes

## Overview
Compare LFP vs. NMC battery technologies in electric vehicles, analyzing energy density, thermal stability, cycle life, replacement costs, and suitability for Indian climate conditions.

## Case Details

Function Focus: Multi-Criteria Product Comparison — manual reasoning, decomposition, and critical judgment (no spreadsheet or AI tool permitted in Phase 1)

Scenario:
You are the analyst at a fictional consultancy ("Praxis Advisors") tasked with answering: Which Electric Vehicle battery technology offers the best long-term value for Indian consumers?. You have a clean, synthetic dataset described below. You must produce a defensible answer using structured reasoning — no tool-assisted shortcut on the first pass.

Dataset Structure:
- brand
- model
- type
- battery_kwh
- range_km
- price_lakhs
- charging_time_mins
- motor_power_watts
- top_speed_kmph
- warranty_battery_years
- fame_subsidy_lakhs
- safety_rating

Tasks:
1. Define the evaluation criteria for the choice and assign weights to each, justified explicitly.
2. Score each alternative by hand against the criteria using the dataset columns.
3. Compute a weighted total and rank the alternatives; show the arithmetic.
4. Run a sensitivity check: change the top two weights by +/10 points and note whether the winner changes.
5. After the manual scoring, redo it in a spreadsheet and reconcile any ranking differences.

Expected Output:
A one-page recommendation memo: criteria & weights, scorecard table, final ranking, sensitivity result.

Evaluation Criteria:
Explicit and justified weights, arithmetic correctness, meaningful sensitivity analysis, defensible final ranking.

## Data Sources

| brand | model | type | battery_kwh | range_km | price_lakhs | charging_time_mins | motor_power_watts | top_speed_kmph | warranty_battery_years | fame_subsidy_lakhs | safety_rating |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Tata | Nexon EV LR | Passenger EV | 40.5 | 465 | 16.5 | 56 | 127 | 150 | 8 | 1.5 | 4-star |
| Tata | Tiago EV | Passenger EV | 24 | 315 | 8.7 | 57 | 74 | 120 | 8 | 1.3 | 4-star |
| MG | ZS EV | Passenger EV | 44.5 | 461 | 23.5 | 50 | 176 | 175 | 8 | 0 | 5-star |
| MG | Comet EV | Passenger EV | 17.3 | 230 | 7.98 | 52 | 50 | 100 | 8 | 0 | 2-star |
| Hyundai | Kona Electric | Passenger EV | 39.2 | 452 | 24.6 | 57 | 136 | 165 | 8 | 0 | 5-star |
| BYD | Atto 3 | Passenger EV | 49.9 | 521 | 28.9 | 54 | 150 | 160 | 8 | 0 | 5-star |
| Ola | S1 Pro | Two-wheeler | 3.97 | 181 | 1.47 | 78 | 8500 | 116 | 3 | 0.5 | N/A |
| Ather | 450X Gen 3 | Two-wheeler | 3.7 | 146 | 1.48 | 72 | 9000 | 105 | 3 | 0.5 | N/A |
| Bajaj | Chetak Urbane | Two-wheeler | 3 | 113 | 1.15 | 65 | 4080 | 70 | 3 | 0.4 | N/A |
| TVS | iQube S | Two-wheeler | 3.4 | 145 | 1.32 | 60 | 8000 | 100 | 3 | 0.4 | N/A |


Full dataset: https://github.com/arora200/aplly_case_db/datasets/051-electric-vehicles (synthetic, 12 records)

## Solution Frameworks
Multi-criteria weighted scoring, pairwise trade-off analysis, cost-benefit decomposition, sensitivity/robustness check

## Solver Guidance & Tutorials
_Solver guidance added by the pipeline (tutorial links) — see `solver_guidance` field._

## What You'll Learn
- Turn vague preferences into weighted criteria
- Build a transparent scorecard
- Test how fragile your winner is

## Tags
EV Battery, LFP, NMC, Battery Technology, India

## Registration Links
Register as Solver / Register as Evaluator