Most of a fleet’s unplanned downtime isn’t randomly distributed: it concentrates on a few components. Three in particular cause the largest share of vehicles stranded at the roadside — battery, tyres, brakes. The good news is that all three leave a readable signal before they fail, if you know where to look.
This article goes into the detail of the three most expensive breakdowns and how predictive maintenance catches them in time, turning a breakdown on a delivery day into a scheduled intervention.
Battery: the number-one breakdown (and the most predictable)
The vehicle that won’t start is one of the most common breakdowns of all — and, paradoxically, one of the easiest to predict. The battery doesn’t fail all at once: it degrades, and its voltage drops progressively over time. A declining voltage trend, especially heading into the cold months (when starting effort increases), is a signal that precedes the failure by weeks.
The data that counts: starting and resting voltage, the trend over time, behaviour at low temperatures. A system that reads them raises an alert when the battery enters the critical zone — before the vehicle won’t start in a yard at 6 a.m.
On electric vehicles the focus shifts to the traction battery: there the parameter is battery state of health (SoH), which measures its remaining capacity. Monitoring it is already predictive maintenance — we cover it in beyond GPS.
Tyres: pressure and wear aren’t a detail
Tyres are at once a safety matter, a fuel matter and a maintenance matter. Under-inflation produces three kinds of damage in parallel: irregular tread wear, higher fuel consumption, and blowout risk at high temperatures or under load.
The key data point is pressure, monitored by TPMS sensors: a drop below threshold is an immediate alert. But there’s a second level, often ignored: driving style accelerates wear. Aggressive cornering and harsh braking wear the tread faster — the same behaviour that weighs on consumption and that’s addressed with eco-driving. Correct pressure, after all, is also one of the fuel-saving levers: the same data works on two fronts.
Brakes: the wear that depends on how you drive
Brakes wear out as a function of how much and how you brake. A fleet with drivers who brake harshly burns through pads and discs far faster than one that drives smoothly. That’s why the braking events recorded by telematics aren’t just a safety data point: they’re a wear predictor for the braking system.
On electrics an extra factor comes in: regenerative braking drastically reduces the use of mechanical brakes, extending their life. It’s one of the reasons an EV’s maintenance plan can’t be the same as a diesel’s — and why driver scoring calibrated to the vehicle type helps read real wear correctly.
What they have in common: the data is already there
Battery, tyres and brakes share one thing: they’re the components whose degradation leaves the most readable trace in the data a connected vehicle already produces. You don’t need exotic sensors — you need voltage, pressure, driving events and diagnostic codes, which arrive via OBD, CAN or Cloud OEM (the detail on sources is in which data you need).
This is the level OptivoTrack sits at: it reads diagnostic codes, generates proactive alerts on thresholds (battery, TPMS) and tracks the driving style that anticipates brake and tyre wear. Not an oracle that guesses the failure to the kilometre, but the signals to act before the component strands the vehicle.
From signal to scheduled intervention
Anticipating a failure on these three components means one concrete thing: turning an unplanned breakdown — the flat battery in the yard, the tyre that blows on the motorway — into a scheduled intervention at the moment of least impact. And that’s where the real saving lies, because the cost of vehicle downtime almost always exceeds that of the spare part.
The logic for placing these checks in the fleet’s maintenance mix — which to keep on the calendar and which to move onto the data — is the subject of the comparison between maintenance strategies.
Frequently asked questions
What’s the most frequent breakdown in a fleet?
The battery is among the most common causes of unplanned downtime, especially in cold months — and also among the most predictable, because voltage drops progressively before failure. Tyres and the braking system follow, both also linked to driving style.
Does driving style really affect breakdowns?
Yes, significantly on brakes and tyres. Harsh braking and aggressive driving accelerate wear. That’s why driving-style data is a wear predictor, as well as a safety and fuel matter.
Do you need extra sensors to anticipate these breakdowns?
For most cases, no: battery voltage, tyre pressure (TPMS), driving events and diagnostic codes arrive from the data the connected vehicle already produces. The detail on data sources is in which vehicle data you need for predictive maintenance.
Go deeper: Predictive maintenance for fleets: how it works and when it pays off — the full picture of data, benefits and implementation.
In the glossary: Predictive maintenance · Battery state of health (SoH) · Eco-driving