Electric vehicles (EVs) utilize various types of rechargeable batteries, each with distinct characteristics in terms of energy density, cost, safety, lifespan, and charging speed.

Two common types of batteries: 
Lithium-Ion (Li-ion) Batteries — Most Common Today
Solid-State Batteries (SSB) — Next Generation

The reliability of an EV battery refers to the probability that the battery will perform its intended function—providing power for propulsion and auxiliary systems—without failure over a specified period and under determined conditions.
The reliability prediction expressed as R(t) represents a constant failure rate under the assumption of an exponential model. EV batteries do not adhere to a simple exponential failure model, as they undergo wear-out due to aging and cycling.

Failure Mechanisms

EV battery reliability is affected by multiple degradation and failure mechanisms:

Capacity fade (loss of usable energy)

Power fade (increased internal resistance)

Thermal runaway (safety failure)

Electrolyte decomposition

Lithium plating and SEI layer growth

Mechanical fatigue of electrodes or current collectors

BMS (Battery Management System) faults

Modeling Battery Reliability

Statistical models, such as the Weibull distribution, lognormal distribution, and Arrhenius models, are used to predict reliability and assess temperature effects.

Physics-of-Failure (PoF) models based on electrochemical degradation kinetics, incorporating temperature, depth of discharge (DoD), and C-rate

Accelerated Life Testing (ALT) for stress tests (temperature, current, voltage extremes) and extrapolate to normal use conditions using Arrhenius or Eyring models.

Key Reliability Stress Factors

The high temperature accelerates SEI growth and electrolyte aging.

Larger Depth of Discharge (DoD) reduces cycle life

High rates (C-rate charging/discharging speed) increase lithium plating and resistance.

Vibration/Shock affects interconnections and mechanical integrity.

Humidity/Contaminants lead to corrosion and leakage current issues.

EV Batteries Improvement Strategies

Thermal management optimization

Smart charging strategies (V2G, adaptive SoC window)

Improved cell chemistry (e.g., solid-state, LiFePO₄)

Advanced BMS fault detection

Predictive maintenance using machine learning